AWS Cloud Computing : Beginner to Industry-Ready

Dive into AWS Cloud from absolute zero, with no prerequisites or prior experience required! This session, led by Vimal Daga, introduces the concept of cloud computing using a unique, engaging real-world story: how Netflix transitioned from DVD rentals to cloud-based video streaming using AWS. Through this storyline, learners will gain a deep, practical understanding of core AWS concepts such as compute, storage, and scalability, and why cloud services have become essential for modern businesses. The session emphasizes hands-on, practical learning and a mindset shift towards how the industry operates in today’s serverless and cloud-native environments.

This training is not designed just for certification purposes but is fully focused on use case–based learning. The session incorporates real-world scenarios, practical demonstrations, and deep dives into cloud solutions used in industry. You’ll be immersed in multiple real industry projects, guided through solving actual challenges using AWS services.

What You'll Learn:

• Fundamental understanding of cloud computing and why it exists.
  

• Core components of computing: RAM, CPU, and program execution.
  

• What a server is and how it powers applications.
  

• The difference between on-premises servers and cloud infrastructure.
  

• The Netflix case study:
  

  • From DVD rentals to video streaming.
    

  • Limitations of physical infrastructure in scaling.
    

  • How AWS enabled global scalability and cost-effective solutions.
    

• Introduction to serverless computing (AWS Lambda) and modern architecture models.
  

• Key AWS concepts: pay-as-you-go, elasticity, scalability, and on-demand infrastructure.
  

• Role of cloud in transforming industries: AI, ML, IoT, Blockchain, App Development.
  

• Why industry-ready knowledge goes beyond certifications and theory.
  

• Structure and approach of the training program, including real project-building and career-focused skills.
  

By the End of This Session, You Will Be Able To:

• Understand the motivation behind cloud computing and infrastructure outsourcing.
  

• Explain the real-world transition of Netflix to the AWS Cloud.
  

• Describe key AWS services such as Lambda and their industry applications.
  

• Articulate the advantages of cloud computing: scalability, flexibility, cost-efficiency, and global reach.
  

• Recognize how cloud computing applies across domains and is vital for various career paths.
  

• Start your AWS journey with a strong foundation built on real-world application, not just theoretical concepts.

  
  

Dive into AWS Cloud from absolute zero, with no prerequisites or prior experience required! This session, led by Vimal Daga, introduces the concept of cloud computing using a unique, engaging real-world story: how Netflix transitioned from DVD rentals to cloud-based video streaming using AWS. Through this storyline, learners will gain a deep, practical understanding of core AWS concepts such as compute, storage, and scalability, and why cloud services have become essential for modern businesses. The session emphasizes hands-on, practical learning and a mindset shift towards how the industry operates in today’s serverless and cloud-native environments.

What You'll Learn:

• Fundamental understanding of cloud computing and why it exists.

• Core components of computing: RAM, CPU, and program execution.

• What is a server, and why it is essential in running applications.

• The difference between local servers and cloud-managed infrastructure.

• Deep dive into the Netflix case study:

  • From DVD rentals to video-on-demand streaming.

  • Infrastructure challenges with physical servers and scalability.

  • The migration journey to AWS Cloud and benefits realized.
    

• Introduction to Cloud Service Providers (CSPs) and serverless architecture.

• Key cloud concepts: Pay-as-you-go, on-demand resources, cost savings, and scalability.

• Relevance of cloud in various domains: AI, ML, IoT, blockchain, web/app development.
  

By the End of This Session, You Will Be Able To:

• Understand the core motivation behind cloud computing and infrastructure outsourcing.

• Explain the Netflix cloud migration case and how it leveraged AWS to scale globally.

• Articulate the benefits of cloud computing like cost-efficiency, scalability, and focus on core business.

• Recognize how cloud is not just for IT professionals but essential for every tech-driven role, from developers to AI engineers.

Begin your AWS journey with a solid foundation in why cloud matters in the real world.

Continue your AWS journey with Vimal Daga as he simplifies the world of cloud computing through real industry applications and practical demonstrations. This session builds upon foundational knowledge and dives into how cloud services, particularly AWS, revolutionize how businesses operate. Using impactful case studies—most notably Netflix’s massive global cloud migration—this session reveals how top companies use AWS services such as EC2 and more than 200+ other offerings to manage scalable, resilient, and efficient digital infrastructures. The course emphasizes practical skill development, real use cases, and introduces learners to the expansive AWS ecosystem through interactive exploration, service-based requirements, and practical tasks.

What You'll Learn:

• What cloud computing truly means and how it is transforming global infrastructure.

• Key AWS concepts: compute power (EC2), server vs. instance terminology, on-demand provisioning.

• Step-by-step guidance on creating your own AWS account.

• Understanding “Pay-as-you-go” and “on-demand” service models.

• Introduction to AWS global infrastructure and 200+ services (e.g., EC2, DynamoDB, Greengrass, Bedrock).

• How Netflix utilizes AWS Cloud to handle global traffic, streaming 15% of the world’s internet bandwidth.

• Exploring AWS industries and solutions used across sectors like finance, automotive, healthcare, gaming, and more.

• Performing real-world research by analyzing AWS customer case studies (e.g., Toyota, AXIS Bank).

• Joining a collaborative LinkedIn group to share learnings, blogs, and insights with 2000+ learners.

• Practical exposure to billing, free tier usage, and real-world AWS coupons and credits.
  

By the End of This Session, You Will Be Able To:

• Launch your first server (EC2 instance) and navigate AWS’s core services with confidence.

• Understand the breadth of AWS’s capabilities across different industries and technical fields.

• Recognize how leading companies like Netflix leverage AWS for scalability, cost reduction, and service delivery.

• Identify use cases and map business needs to AWS solutions effectively.

• Perform industry research and create blog posts or presentations demonstrating AWS adoption and value.

• Be equipped with the knowledge to explore cloud migration strategies and pitch cloud solutions in real-world scenarios.

Step into a transformative AWS Cloud learning experience with Vimal Daga that goes beyond traditional cloud training. This session is not just about understanding AWS services—it's about mastering real-world problem solving, production-grade thinking, and strategic IT decision-making. You will explore not only how to use the cloud, but why industry leaders make critical cloud choices. Key concepts such as serverless architecture, cost optimization, and infrastructure management are introduced with a practical mindset shift that equips you to think like a consultant, not just a developer. Through real industry examples and demos, you'll gain insight into how AWS can reduce operational burdens and costs—making you indispensable in any technology-driven role.

What You'll Learn:

• Real meaning of serverless: why it's important and how it transforms IT operations.

• The difference between self-managed infrastructure and cloud-managed infrastructure.

• Importance of compute resources (RAM, CPU) in running applications.

• Who holds the responsibility in IT operations—cost, maintenance, infrastructure.

• How cloud service providers (CSPs) like AWS reduce the burden of management and offer pay-as-you-go pricing models.

• How to think like a tech strategist: reducing cost and management load using architecture planning.

• The role of cloud engineers in cost-saving and optimization initiatives for companies.

• Why learning AWS through the lens of real use cases and cross-industry integration brings faster career growth.

• Understanding computation complexity and optimizing technical resources efficiently.

• Transitioning from being a "techie executor" to a solution-driven architect.
  

By the End of This Session, You Will Be Able To:

• Grasp the critical concepts of serverless computing, cost optimization, and infrastructure delegation.

• Understand cloud responsibilities from both technical and strategic business perspectives.

• Create architecture plans that reduce company costs and eliminate operational burdens.

• Begin adopting the mindset of a cloud consultant or architect, not just a cloud user.

• Communicate the value of AWS Cloud to stakeholders, using real examples like Netflix and other industry players.

• Build a foundation for leading cloud transformation initiatives in any organization.

In this pivotal session led by Vimal Daga, you will go deep into the heart of AWS Cloud computing—exploring the practical challenges and solutions around EC2 instances and the evolution to serverless architecture. Through real-time demos and scenario-based discussion, this training bridges the gap between traditional server provisioning and the modern, cost-optimized, fully managed serverless model. Learn why manual infrastructure management can be expensive, error-prone, and inefficient—and how AWS Serverless services overcome those limitations. The session focuses not only on launching instances, but also on developing a mindset that prioritizes automation, optimization, and exponential career growth through smart architecture decisions.

What You'll Learn:

• In-depth walkthrough of EC2 service: launching, configuring, and running OS instances.

• Responsibilities of AWS vs. the cloud engineer when using EC2.

• Real-world challenges of manual infrastructure management (cost, delays, errors, dependencies).

• Runtime management using languages like Python, installing dependencies, and executing custom scripts.

• Understanding the billing model: EC2 hourly billing vs. compute-based serverless billing.

• The need for optimization in modern cloud environments.

• Transitioning to serverless architecture: fully managed services and on-demand execution.

• Real-time demo showing how to deploy, manage, and run applications using EC2 vs. Serverless.

• Concept of "Compute Time" and how serverless reduces cost drastically.

• Introduction to “Serverless” as a fully managed service paradigm with no need for OS handling.
  

By the End of This Session, You Will Be Able To:

• Understand the full EC2 lifecycle: from provisioning to application deployment.

• Identify the hidden costs and operational overheads of manually managed cloud resources.

• Evaluate when to use EC2 vs. when to shift to serverless computing based on app requirements.

• Describe the benefits of serverless computing: pay-per-execution, scalability, and zero server management.

• Create highly optimized cloud strategies that reduce cost and increase speed-to-execution.

• Start thinking like a cloud architect—focusing on optimization, automation, and ROI for your company or startup.

In this session with Vimal Daga, explore one of the most transformative technologies in modern cloud computing—AWS Lambda. Learn how serverless architecture and function-as-a-service (FaaS) models enable rapid, cost-effective execution of individual functions without managing any infrastructure. By contrasting monolithic and microservices-based architectures, the training emphasizes how serverless systems drive innovation, save computing resources, and minimize cost. This session introduces you to AWS Lambda as the backbone of real-world serverless deployments—empowering you to deploy logic, not infrastructure, and enabling fine-grained billing per function execution.

What You'll Learn:

• Understanding the difference between managed, fully managed, and serverless services.

• Core AWS services categorized by compute needs (EC2 vs Lambda).

• The concept of Lambda as a Function-as-a-Service (FaaS) platform.

• How AWS Lambda allows you to "Run Code Without Thinking About Servers."

• Billing in serverless models: pay only for compute time, not for idle time.

• Real-world relevance: How companies adopt Lambda for event-driven, low-latency applications.

• The difference between monolithic vs microservices architecture.

• Microservices = Functions: How developers build modern applications using modular logic.

• Deploying individual functions (like Play, Stop, Resume) rather than whole applications.

• Benefits of serverless design: reduced RAM/CPU consumption, zero idle costs, greater scalability.

• Use cases across industries and why Lambda is foundational to most modern cloud-native projects.
  

By the End of This Session, You Will Be Able To:

• Explain and differentiate between EC2 and Lambda in terms of responsibility, cost, and use case.

• Understand the importance of serverless and microservices in modern cloud design.

• Utilize AWS Lambda to deploy individual functions with precision and efficiency.

• Architect cloud applications using modular, event-driven, serverless services.

• Apply cloud-native principles to build scalable, optimized, and cost-effective solutions.

• Recognize Lambda’s central role in real-world serverless architectures and enterprise use cases.

In this session, Vimal Daga takes a deep dive into AWS Lambda, focusing on its significance in building modern cloud-native architectures. You’ll explore how organizations use serverless computing and function-as-a-service (FaaS) to drastically reduce infrastructure management and operational costs. The session compares EC2 and Lambda from real-world use case, cost, and efficiency perspectives—highlighting Lambda’s role in scaling applications, minimizing idle compute time, and enabling granular execution billing. You'll also learn how microservices and modular design drive the serverless revolution, allowing engineers to run code in response to events without provisioning servers.

What You'll Learn:

• Introduction to cloud-native architecture and microservices.
  

• How to create and deploy a Lambda function from scratch using Python.
  

• The difference between EC2 (managed) vs. Lambda (fully managed/serverless).
  

• How to deploy and invoke Lambda functions using the AWS Management Console.
  

• Execution billing model: RAM usage and CPU time-based cost calculation per millisecond.
  

• Practical understanding of the "invoke" concept in Lambda (function call per request).
  

• Introduction to the AWS Pricing Calculator for service cost estimation.
  

• How to evaluate and compare costs between Lambda and EC2 for identical tasks.
  

• The role of Lambda in reducing manual infrastructure management, cost, and latency.
  

• Key terminologies: Serverless, Function-as-a-Service (FaaS), Invoke, Cloud-Native, Microservices.
  

By the End of This Session, You Will Be Able To:

• Launch and configure your first AWS Lambda function with event-based execution.
  

• Understand and articulate the cost differences between Lambda and EC2 in practical scenarios.
  

• Evaluate when to use serverless architecture over traditional instance-based compute.
  

• Apply the AWS Pricing Calculator to simulate cost estimates for real-world cloud deployments.
  

• Explain the principles of cloud-native architecture and microservice-based design.
  

Think critically about optimization, performance, and cost-efficiency when selecting cloud services.

Join Vimal Daga in this hands-on AWS training session as he deepens your understanding of EC2, Lambda, and introduces essential services like CloudWatch and API Gateway. Designed for learners preparing to become industry-ready, this session builds on previously covered serverless concepts and demonstrates how to deploy real-world web applications using EC2, followed by a transition to serverless execution using Lambda. Learn how enterprises are adopting cloud-native architectures to enhance performance, minimize manual effort, and enable automatic scalability. This session is structured around real use cases, demo-driven learning, and the evolving cloud trends in today’s and tomorrow’s job market.

What You'll Learn:

• Review and extension of EC2: launching Linux-based servers using Amazon Linux.
  

• Responsibilities in EC2 deployments: setting up runtime environments (e.g., PHP, Python), interpreters, and web servers manually.
  

• Understanding the concept of serverless and how Lambda reduces developer responsibilities.
  

• Differences in responsibilities and cost between EC2 (self-managed) and Lambda (fully managed).
  

• Hosting a static website using EC2: security group setup, web server configuration, HTTP protocol handling.
  

• Introduction to API Gateway as a powerful serverless interface for connecting services.
  

• Introduction to CloudWatch for monitoring, logging, and troubleshooting cloud services.
  

• Real-world use case: hosting a web application written in PHP using EC2, and learning how the same could be optimized using serverless tools.
  

• AWS best practices around region selection, latency considerations, and infrastructure planning.
  

By the End of This Session, You Will Be Able To:

• Confidently launch and configure EC2 instances with a real-world website deployment.
  

• Explain the full lifecycle of a traditional EC2 deployment and the overhead it involves.
  

• Transition your thinking toward cloud-native and serverless-first architecture principles.
  

• Understand and prepare for hands-on usage of Lambda, CloudWatch, and API Gateway in upcoming sessions.
  

• Choose the appropriate AWS services based on real business use cases, cost, and scalability needs.
  

Explain the differences between managed and fully managed services in the AWS ecosystem.

In this in-depth session, Vimal Daga provides a hands-on walkthrough of deploying a live website using AWS EC2, while simultaneously introducing critical cloud management concepts through CloudWatch—AWS’s monitoring and observability service. The session begins by demonstrating how to launch, configure, and host a PHP-based website on an EC2 instance, highlighting the step-by-step server setup required in self-managed infrastructure. It then transitions into the use of CloudWatch metrics to monitor system performance in real-time, with visualizations and frequency-based tracking of CPU, memory, disk, and network usage. This class emphasizes the real-world responsibilities of cloud engineers and illustrates how AWS tools can be used to streamline, observe, and optimize web deployments.

What You'll Learn:

• Full deployment cycle of a PHP-based website on an EC2 Linux instance.
  

• Step-by-step setup: installing PHP, Apache web server, and configuring runtime.
  

• Web hosting fundamentals: serving a dynamic website via HTTP and managing Linux file structure.
  

• Creating dynamic responses with PHP to identify and display client metadata (IP, browser, OS).
  

• Understanding EC2 resource utilization: RAM, CPU, disk I/O, and network bandwidth.
  

• Introduction to AWS CloudWatch and its role in real-time infrastructure monitoring.
  

• Visualizing server metrics: spikes in CPU usage triggered by user interaction.
  

• Monitoring granularity: default 5-minute intervals and enabling 1-minute detailed monitoring.
  

• Real-time performance tracking through EC2’s embedded CloudWatch dashboards.
  

• Cost-awareness of enhanced monitoring options and how to evaluate their necessity.
  

By the End of This Session, You Will Be Able To:

• Deploy a live website on EC2 and manage all server-level configurations for hosting.
  

• Analyze and interpret CloudWatch graphs to understand server load and usage patterns.
  

• Use EC2 and CloudWatch in tandem to create observability-driven deployments.
  

• Understand the trade-offs between traditional infrastructure and serverless alternatives.
  

• Set up alerts and metric-based decision systems for better operational oversight (to be explored further in upcoming sessions).
  

• Appreciate the importance of monitoring frequency and its effect on cost and real-time actionability.

In this advanced session on serverless computing, Vimal Daga provides an industry-level deep dive into AWS Lambda, showcasing how it powers scalable, event-driven applications without any infrastructure management. By contrasting Lambda with EC2 and traditional web servers, this class explains why Lambda is the go-to choice for high-concurrency, real-time applications used by global tech leaders like Netflix and Hotstar. Participants will walk through a real-world example of migrating a PHP-based application from EC2 to Lambda, explore code execution flow, and understand the benefits of auto-scaling, pay-per-invoke, and unlimited compute capacity that Lambda offers.

What You'll Learn:

• Recap of serverless principles using AWS Lambda.
  

• Comparison of Lambda vs. traditional web hosting using EC2.
  

• Step-by-step creation of Lambda functions using Python.
  

• Understanding runtime environments, language support, and how Lambda abstracts server infrastructure.
  

• Migrating code logic (e.g., PHP/HTML) from EC2 to Lambda for backend execution.
  

• Live demonstration of Lambda function execution without any OS or server setup.
  

• Lambda vs. online interpreters: major limitations of free environments vs. scalable cloud infrastructure.
  

• Understanding concurrent executions and the need for scalable compute power in real applications (e.g., World Cup live stream on Hotstar).
  

• Detailed explanation of auto-scaling and how Lambda handles millions of requests per second.
  

• Billing model of Lambda: pay-as-you-go per millisecond based on RAM/CPU utilization.
  

By the End of This Session, You Will Be Able To:

• Build and deploy serverless functions using AWS Lambda without provisioning infrastructure.
  

• Migrate workloads from EC2 to Lambda for cost efficiency and elasticity.
  

• Explain the value of serverless computing in high-traffic scenarios (e.g., streaming platforms, e-commerce).
  

• Understand how Lambda auto-scales with demand and returns to zero cost when idle.
  

• Differentiate Lambda from online code runners and traditional VMs in terms of scalability and reliability.
  

• Strategize the use of Lambda in real-world enterprise environments for both frontend and backend processes.

Join Vimal Daga as he walks you through practical, hands-on training on AWS Lambda using Python. This session dives deep into serverless computing, providing clarity on how to build and deploy scalable, cost-effective applications in the cloud. You’ll explore the relationship between AWS Lambda, CloudWatch, and API Gateway, while gaining essential knowledge on Python functions, Lambda handler configuration, and function invocation. Whether you're a beginner or someone aiming to understand real-world AWS architecture, this course demystifies the complexities of Lambda execution, monitoring, and web app deployment — all without writing complex backend infrastructure code. Learn industry practices, understand cloud engineer responsibilities, and build your confidence in integrating Python code with AWS services for modern development scenarios.

What You'll Learn:

• Deep understanding of AWS Lambda and its function-based architecture
  

• Writing Python functions specifically for Lambda environments
  

• Understanding and configuring Lambda handler functions
  

• Practical insights into CloudWatch for monitoring metrics and performance
  

• Managing Python function inputs (event, context) and their relevance
  

• Working with multiple functions and files inside a Lambda environment
  

• Understanding execution context, memory usage, and Lambda error handling
  

• Deploying Lambda functions with real-time testing and troubleshooting
  

• Introduction to public access of Lambda through API Gateway
  

• Key differences between EC2 and Lambda, and when to use what
  

• Developer vs. Cloud Engineer responsibilities in serverless application development
  

By the End of This Session, You Will Be Able To:

• Confidently configure and deploy Python-based AWS Lambda functions
  

• Handle function invocation, errors, and memory usage like a pro
  

• Understand and modify handler settings to control function execution
  

• Collaborate effectively with developers by knowing what code standards and inputs Lambda requires
  

• Use CloudWatch to monitor and improve Lambda performance
  

• Build the foundation to deploy public-facing applications using Lambda + API Gateway
  

• Transition from a traditional server-based mindset to a modern serverless architecture approach

Join Vimal Daga as he delves deeper into AWS Lambda and its real-world integrations. This session focuses on serverless execution and effective monitoring using AWS CloudWatch. Designed for learners aiming to master cloud-native application development, the course unpacks how Lambda operates without server management and how CloudWatch plays a pivotal role in logging and troubleshooting. You'll explore the intricacies of Lambda's runtime behavior, learn the significance of print vs return statements, and discover how to access historical logs using CloudWatch for improved visibility. This class prepares you to build and manage resilient, cost-effective serverless applications with an eye on performance and diagnostics.

What You'll Learn:

• The fundamentals of AWS Lambda and its serverless architecture
  

• Understanding Lambda's pricing model and free-tier benefits
  

• Writing and deploying Python functions in Lambda
  

• Differences between return and print in Lambda and where outputs go
  

• Importance of structuring code within functions and using arguments
  

• Introduction to CloudWatch and how it integrates with Lambda
  

• Logs vs Metrics: storing and analyzing historical data
  

• Navigating CloudWatch Logs: log groups, log streams, and real-time monitoring
  

• Debugging and troubleshooting Lambda failures using log outputs
  

• Best practices for printing information intentionally to CloudWatch
  

• Navigating AWS UI for fast access to monitoring and logs
  

By the End of This Session, You Will Be Able To:

• Understand and leverage AWS Lambda as a core part of your cloud architecture
  

• Write structured and effective Python functions suitable for Lambda execution
  

• Differentiate between logs and output responses, and where each appears
  

• Utilize CloudWatch Logs to track runtime behavior and historical events
  

• Troubleshoot Lambda functions using real-time and historical logging data
  

• Confidently deploy, monitor, and maintain serverless functions
  

• Prepare for advanced integrations with other AWS services like API Gateway
  

• Recognize the indispensable role of Lambda in modern cloud-based architectures

Join Vimal Daga as he simplifies and demystifies one of the most powerful yet often misunderstood AWS services—API Gateway. This course uses real-world analogies (like how Google search works) to explain how API Gateway acts as an intelligent middleman between external users and your backend programs or services, including Lambda. You'll explore how major tech companies like Google, Netflix, and Facebook use API Gateways to manage complex infrastructures, route user requests, enforce usage policies, and deliver secure, scalable web services. This session builds a solid foundational understanding of how APIs and API Gateway function, and sets the stage for integrating them with serverless applications like AWS Lambda in subsequent sessions.

What You'll Learn:

• What an API is and how it enables programmatic access to backend services
  

• Deep conceptual understanding of API Gateway and its real-world use cases
  

• How large-scale systems (e.g., Google, Netflix) use API Gateways for intelligent request routing
  

• The relationship between endpoints, routes, paths, and backend services
  

• How API Gateway acts as a security layer and access controller
  

• The difference between server IPs and API Gateway entry points
  

• Benefits of API Gateway: centralized access, user-level traffic control, request monitoring
  

• How multiple backend services (e.g., Gmail, Search, Ads) are exposed via a single URL using routes
  

• API Gateway as the backbone of subscription models, rate limiting, and analytics
  

• How API Gateway simplifies complexity and enhances scalability
  

By the End of This Session, You Will Be Able To:

• Clearly understand the role of API Gateway in modern web architecture
  

• Visualize how client requests are processed, routed, and managed by API Gateway
  

• Explain the concept of routes/endpoints and how they connect to backend services
  

• Appreciate the real-world importance of API Gateway in systems like Google and Netflix
  

• Build the mental model needed to integrate API Gateway with AWS Lambda
  

• Recognize how to use API Gateway for authentication, monitoring, filtering, and throttling
  

• Begin designing your own scalable APIs for various use cases including serverless web apps
  

• Understand the strategic value of centralizing access and control through API Gateway

Dive into the world of serverless architecture with this hands-on course led by Vimal Daga. This session focuses on mastering AWS API Gateway and its integration with AWS Lambda, demonstrating how to build scalable, cost-effective backend systems without managing servers. With a practical and simplified approach, you'll learn how API Gateway acts as a reverse proxy, directing traffic to different backend services such as Lambda functions or EC2 instances. Vimal explains how serverless automatically handles traffic spikes by dynamically scaling resources, offering robust performance without manual intervention. This course not only demystifies API Gateway but also shows how to use it to securely expose backend services (e.g., Lambda functions) to the internet, including creating routing rules for different endpoints. The session concludes with a real-time demo where you learn to trigger Lambda functions via HTTP endpoints, a critical skill in modern cloud-native application development.

What You'll Learn:

• Concept and role of API Gateway in a serverless architecture.

• Serverless benefits like auto-scaling, reduced operational overhead, and cost efficiency.

• API Gateway as a reverse proxy and how it handles traffic to backend services.

• Practical use of API Gateway to invoke Lambda functions over the internet.

• How API Gateway allows public access to backend services without exposing internal systems.

• Connecting multiple Lambda functions to different API Gateway routes.

• Understanding triggers and auto-invocation of Lambda using API Gateway.

• Logging and debugging Lambda functions using CloudWatch.

• Building RESTful endpoints with API Gateway connected to serverless functions.
  
  

By the End of This Session, You Will Be Able To:

• Confidently set up and configure API Gateway to serve as a public entry point for your backend applications.

• Automatically invoke Lambda functions via specific HTTP routes.

• Monitor, debug, and verify execution through AWS CloudWatch logs.

• Understand and implement real-world scenarios involving API Gateway and Lambda to build scalable, secure, serverless applications.

• Apply this knowledge to build internet-facing services without exposing your cloud infrastructure.

Step into the world of serverless computing with this powerful hands-on session led by Vimal Daga. Learn how to build a fully functional, scalable, and serverless web application using AWS Lambda and API Gateway without ever logging into an EC2 instance or managing traditional servers.

This training covers everything from setting up REST APIs using API Gateway to integrating those APIs with backend AWS Lambda functions. You’ll discover how client requests trigger backend logic, process data, and return responses in real-time—all in a serverless environment. With a focus on performance, cost-efficiency, and scalability, this course teaches you how modern cloud-native applications are developed using AWS services.

You'll walk through real implementation steps, configuration insights, and testing strategies to deploy a web application that is lightweight, scalable, and globally accessible.

What You'll Learn:

• What REST APIs are and how API Gateway supports them.
  

• The difference between various API methods: GET, POST, etc.
  

• Creating REST API paths/routes (like /mail, /search) in API Gateway.
  

• Mapping API Gateway routes to AWS Lambda functions.
  

• Deploying APIs and obtaining publicly accessible endpoints.
  

• Understanding HTTP methods and how client-server interaction works.
  

• Testing Lambda-triggered functions via browser-based public URLs.
  

• Observing Lambda function usage metrics using AWS CloudWatch.
  

• Real-time function edits and updates with instant deployment.
  

• How API Gateway and Lambda scale automatically to handle multiple requests.
  

• Benefits of serverless architecture: no infrastructure management, reduced cost, and scalability.
  

By the End of This Session, You Will Be Able To:

• Build and deploy a RESTful API using AWS API Gateway.
  

• Integrate API routes with Lambda functions to create a functioning backend.
  

• Access your Lambda-based application using public URLs.
  

• Modify and test serverless functions in real time without downtime.
  

• Analyze traffic, invocations, and logs using AWS CloudWatch.
  

• Deliver scalable applications with zero server maintenance.
  

• Understand the role of API Gateway as a reverse proxy and routing mechanism.
  

• Appreciate the architecture of modern serverless applications built by combining multiple AWS services.

This unique and practical session introduces an advanced and industry-relevant AWS concept—enabling users to interact with AWS services like EC2 without logging into the AWS Console or knowing the credentials. Led by Vimal Daga, the session focuses on building a self-service automation project, where team members can launch EC2 instances in someone else's AWS account securely—without access to credentials—by leveraging event-based automation and integrating multiple AWS services.

This hands-on course diverges from traditional AWS certification-oriented teaching, focusing instead on how modern companies automate infrastructure provisioning using APIs, CLI, and serverless triggers. Whether you're a developer, DevOps engineer, or cloud enthusiast, this session equips you with foundational skills needed to architect and automate real-world cloud infrastructure.

What You’ll Learn:

The Real-World Use Case:

• How to allow a team member to launch an EC2 instance without logging into AWS.
  

• Creating a self-service architecture to enable controlled access to resources.
  

• Understanding why companies do not use manual AWS Console interactions in production.
  

Core Concepts Introduced:

• Cloud Access Models:
  

  • Web UI (Console)
    

  • CLI (Command Line Interface)
    

  • API-based Access (most used in production automation)
    

• Manual vs. Automated Approaches:
  

  • Manual method using AWS Console is slow, error-prone, and non-scalable.
    

  • Automated method using API and scripts enables faster, consistent, and error-free deployments.
    

• Why Event-Based Automation:
  

  • Avoid sharing credentials.
    

  • Enable safe resource provisioning through pre-approved backend logic.
    

  • Use serverless and event-driven components to scale operations without infrastructure management.
    

Implementation Highlights:

• Overview of how real companies like Netflix and Amazon achieve cloud automation.
  

• Learn the integration of multiple AWS services like Lambda, API Gateway, IAM, and EC2 to implement this project.
  

• Use of event triggers and APIs to perform tasks traditionally done via AWS Console.
  

• Lays the foundation for building advanced projects in AI, ML, IoT, and serverless computing.
  

By the End of This Session, You Will Be Able To:

• Explain how users can perform actions in AWS without login access.
  

• Set up a secure, event-driven EC2 provisioning workflow.
  

• Understand the limitations of manual cloud usage and the benefits of automation.
  

• Use AWS automation techniques to develop scalable, production-grade cloud infrastructure.
  

• Shift from GUI-based learning to code-driven, real-world automation thinking.

Step into the future of cloud computing with this pioneering session that bridges Generative AI and Cloud Automation. This course—led by Vimal Daga—introduces you to a groundbreaking concept where a Generative AI system (like ChatGPT) can design infrastructure strategies based on project requirements and budgets, and then automate the entire cloud setup process in AWS using Python and Boto3.

The session walks through building a voice-command or prompt-driven infrastructure-as-code solution. You’ll witness how traditional manual tasks (like launching EC2 instances) evolve into intelligent, automated processes that respond to spoken input or chat instructions. This real-world project will teach you how to integrate automation, optimization, cost control, and AI decision-making—all within a practical AWS environment.

What You’ll Learn:

The Real-World Use Case:

• Automate cloud resource provisioning based on inputs like budget, performance needs, and business goals.
  

• Let Generative AI recommend infrastructure plans and immediately convert those plans into executable code.
  

• Understand how a human request like “Launch a cost-optimized EC2 instance for a production app in Mumbai” can be turned into real AWS infrastructure.
  

Key Concepts and Innovations:

• Beyond Automation:
  

  • Traditional automation is limited by human-designed scripts.
    

  • This session introduces GenAI + Automation = “GenAI Ops.”
    

• Generative AI Integration:
  

  • Use tools like ChatGPT to design cloud strategies.
    

  • Real-time conversion of AI suggestions into Python code.
    

• Automation Implementation:
  

  • Use Python and the Boto3 AWS SDK to launch EC2 instances from a script.
    

  • Install and configure tools like Anaconda and Jupyter Notebook for development.
    

  • Understand how AWS services (EC2, Lambda, etc.) are programmatically controlled.
    

• Practical Tools and Techniques:
  

  • How to install Python using Anaconda.
    

  • Using Jupyter Notebook to run Python scripts.
    

  • How to install and use Boto3, the AWS SDK for Python.
    

  • Structure of Python programs to automate AWS tasks.
    

• Code Deep Dive:
  

  • Writing and executing Python code to launch EC2 instances.
    

  • Using boto3.resource("ec2") to interface with EC2 service.
    

  • Understanding required parameters like AMI ID and instance type.
    

  • Error handling, default parameters, and practical debugging tips.
    

By the End of This Session, You Will Be Able To:

• Use Generative AI to assist in AWS infrastructure planning and decision-making.
  

• Write Python scripts using Boto3 to automate cloud setup tasks.
  

• Launch AWS EC2 instances without using the AWS Console.
  

• Install, configure, and use Anaconda, Jupyter, and Boto3 for AWS automation.
  

• Embrace real-world DevOps practices through AI-enhanced cloud automation workflows.
  

• Shift from GUI-based cloud usage to intelligent automation driven by code and AI.

This hands-on training session introduces learners to the practical use of AWS Cloud using Python and the Boto3 SDK. Designed for those with basic to intermediate understanding of cloud concepts, the session dives straight into automation by teaching how to launch and manage AWS EC2 instances programmatically.

Led by Vimal Daga, the session focuses on real-time problem-solving and building automation solutions rather than just theoretical concepts. It covers the key AWS elements such as Amazon Machine Images (AMIs), EC2 instance management, access key handling, and client vs. resource modes in Boto3. The entire session is filled with live demonstrations, scripting walkthroughs, and insightful explanations of how cloud resources are manipulated programmatically.

What You'll Learn:

• What AMIs (Amazon Machine Images) are and how they represent OS configurations.
  

• Understanding and using AMI IDs vs. human-readable OS names.
  

• Launching EC2 instances using Python scripts via Boto3.
  

• The significance of parameters like MinCount and MaxCount when launching instances.
  

• Automation of EC2 provisioning without manual console interaction.
  

• Authentication in Boto3 using Access Key ID and Secret Access Key.
  

• How to store and securely manage AWS credentials in scripts or your system.
  

• Using Boto3 resource and client objects: differences, use-cases, and benefits.
  

• Fetching EC2 instance metadata like instance ID, architecture, IP address, and type.
  

• Deleting (terminating) EC2 instances using Python scripts.
  

• Using describe_instances() and terminate_instances() with Boto3 client.
  

• Importance of automation for scalability (e.g., launching thousands of instances).
  

By the End of This Session, You Will Be Able To:

• Launch EC2 instances using Python code and automate the provisioning process.
  

• Understand and work with AMIs and EC2 instance metadata.
  

• Handle AWS credentials securely and programmatically.
  

• Retrieve details of instances without using the AWS console.
  

• Terminate EC2 instances via Boto3 scripts.
  

• Differentiate between Boto3 resource and client objects and know when to use each.
  

• Appreciate the power of Python automation in real-world AWS cloud operations.

Empower your teams to launch AWS EC2 instances securely and seamlessly—without needing AWS login credentials. In this session led by Vimal Daga, you'll dive into an advanced and real-world scenario: enabling external team members or automated systems to launch and terminate EC2 instances through API endpoints, using AWS Lambda and API Gateway.

This session is designed to demonstrate secure, serverless automation of AWS services. You’ll build a system that lets anyone (or anything) launch an EC2 instance just by hitting a URL—perfect for DevOps, AI model testing, self-service provisioning, or scalable app infrastructure. This course emphasizes integrating multiple AWS services programmatically, unlocking powerful automation workflows used across modern industry environments.

What You'll Learn:

• How to allow external users or apps to launch EC2 instances without sharing AWS credentials.
  

• Creating a Lambda function to run Python code that connects to EC2 and launches instances.
  

• Integrating AWS Lambda with API Gateway to expose public URLs for automated triggers.
  

• Implementing a secure and serverless infrastructure using Lambda.
  

• Passing login credentials (Access Key and Secret Key) securely inside the Lambda environment.
  

• Handling timeouts, memory configuration, and execution settings for Lambda functions.
  

• Triggering EC2 launches via browser, mobile app, or external systems through API calls.
  

• Monitoring and debugging Lambda functions and EC2 responses.
  

• Creating self-service systems for internal teams like developers or AI researchers.
  

• Expanding automation with termination endpoints and parameterized requests.
  

By the End of This Session, You Will Be Able To:

• Develop Lambda functions that launch EC2 instances using Boto3 and Python.
  

• Expose Lambda functionality via REST APIs using AWS API Gateway.
  

• Enable secure, no-login EC2 instance launches via public endpoints.
  

• Configure Lambda timeouts, RAM, and settings for cloud performance.
  

• Build infrastructure-agnostic mobile or web apps to control AWS EC2 operations.
  

• Understand real industry use cases like AI model testing, mobile backend integration, and self-service provisioning.
  

• Implement multi-service AWS integrations with a focus on security, scalability, and simplicity.

Get introduced to the power of real-time notifications in AWS using Simple Notification Service (SNS). This session, led by Vimal Daga, offers a practical and highly relatable approach to building notification systems within the AWS ecosystem. Whether you're dealing with billing alerts, EC2 instance state changes, or broader cloud activity, this course shows you how to keep your team informed via email, SMS, or other channels—just like receiving mobile app alerts.

This training forms the foundation for advanced topics like Event-Driven Architecture (EDA), which will be explored in upcoming sessions. Today’s focus is on understanding how SNS works, how it can be integrated with other AWS services, and how to configure notifications to reach the right stakeholders automatically. With hands-on examples and live demonstrations, you'll see exactly how to configure topics, subscriptions, and testing mechanisms using AWS SNS.

What You'll Learn:

• Real-world understanding of notification systems using AWS SNS.
  

• Why notifications are important in modern cloud systems (e.g., billing alerts, EC2 shutdowns).
  

• What SNS (Simple Notification Service) is and its role in AWS architecture.
  

• Creating topics in SNS to represent different use cases (billing, EC2 events, etc.).
  

• Subscribing email IDs and phone numbers to specific topics.
  

• Understanding and using SNS protocols: email, SMS, and more.
  

• How to confirm subscriptions and ensure secure delivery.
  

• Sending test notifications to verify setup.
  

• Preparing SNS for integration with event sources like billing, EC2, or API Gateway.
  

• Laying the groundwork for Event-Driven Architecture (EDA) with SNS.
  

By the End of This Session, You Will Be Able To:

• Set up and configure AWS SNS to send notifications across multiple channels.
  

• Create use-case-specific topics and manage subscriptions for email and SMS.
  

• Confirm and test your notification pipeline from AWS to real-world devices.
  

• Understand the concept of publishing messages to a topic.
  

• Know when and how SNS integrates with other AWS services for alerting.
  

• Prepare your system for advanced workflows like Event-Driven Architectures (covered in the next session).
  

• Improve team collaboration and cloud visibility through automated notifications.

In this session led by Vimal Daga, dive deeper into integrating AWS services to build intelligent, real-time notification systems. This training focuses on enhancing your serverless workflows by sending alerts (via email or SMS) whenever an EC2 instance is launched—automatically and without manual intervention.

Building on previous sessions that used API Gateway and Lambda to launch EC2 instances, this course adds another powerful layer: AWS Simple Notification Service (SNS). You will learn how to write Python code using Boto3 to trigger SNS notifications from within a Lambda function or local script. This solution keeps your team informed at all times, even if instances are launched in the middle of the night.

The course bridges the concepts of automation, serverless design, and cloud monitoring, empowering you to build real-world, industry-level notification mechanisms using AWS-native tools.

What You'll Learn:

• How to send email and SMS notifications using AWS SNS.
  

• Connecting Lambda to SNS for real-time event-driven messaging.
  

• Writing Python (Boto3) code to publish SNS messages.
  

• Using topics and subscriptions in SNS to route messages to relevant recipients.
  

• Understanding the structure of Amazon Resource Names (ARNs) and their use in SNS topics.
  

• Building event-aware Lambda functions that notify teams upon EC2 instance launch.
  

• Testing SNS notifications locally before deploying them to Lambda.
  

• Using SNS to notify internal teams, not end-users, for infrastructure-level changes.
  

• Introduction to the difference between SNS (internal alerts) and SES (customer-facing emails).
  

• Real-world scenarios where cloud automation improves operational efficiency.
  

By the End of This Session, You Will Be Able To:

• Configure and use AWS SNS for sending internal notifications.
  

• Programmatically publish messages to an SNS topic using Python and Boto3.
  

• Integrate SNS messaging into your Lambda functions for real-time alerts.
  

• Understand the importance of ARNs and how to use them in topic configurations.
  

• Differentiate between SNS for internal alerting and SES for external user communication.
  

• Develop alert systems for EC2 instance launches that notify teams instantly via email.
  

• Apply this knowledge in production scenarios such as server provisioning, cost monitoring, and internal IT automation.

Course Description:
Dive into the core concept of Event-Driven Architecture (EDA)—a foundational pillar of modern cloud-native applications. In this highly practical session led by Vimal Daga, you'll explore how real-time events, such as a successful online purchase or a failed transaction, trigger backend workflows like sending emails, SMS, or notifications. Rather than teaching AWS services in isolation, this class showcases how EDA powers real-world use cases across platforms like Amazon and Netflix.

You’ll discover how AWS helps eliminate the need for manual coding and heavy backend infrastructure by offering pre-built cloud services to handle these events automatically. This session emphasizes how industry works, not how certification books teach—making it ideal for students, professionals, and tech enthusiasts looking to become truly industry-ready.

What You'll Learn:

• Deep understanding of Event-Driven Architecture (EDA) and why it matters in today’s cloud ecosystem.
  

• Real-life e-commerce use case:
  

  • What happens when a user clicks “Buy Now”?
    

  • How success/failure events trigger customized workflows (email, SMS, push notifications).
    

• Key EDA Concepts:
  

  • Event: a real-world trigger (e.g., transaction success or failure).
    

  • Action: system response to an event (e.g., send email/SMS).
    

• Traditional method: Writing code in Python/JavaScript to manage these events manually.
  

• Cloud-native method:
  

  • How AWS replaces developers with managed, no-code/low-code services.
    

  • Setting up event-based workflows using serverless infrastructure.
    

• Business benefit: no upfront infrastructure, pay-as-you-go model, faster time to market.
  

• Why EDA is essential for apps in AI, ML, IoT, and real-time data systems.
  

• Highlighting the skills gap between certification-based learning and industry expectations.
  

By the End of This Session, You Will Be Able To:

• Explain what Event-Driven Architecture is and its role in cloud computing.
  

• Map common user actions to backend event flows in real-world applications.
  

• Understand how AWS automates event handling without requiring manual backend coding.
  

• Identify AWS services that support EDA and reduce developer dependency.
  

• Apply EDA concepts to build scalable, responsive, and intelligent cloud-native applications.
  

Shift your mindset from theoretical learning to real-world, use case–oriented cloud thinking.

Course Description:
This session continues the exploration of Event-Driven Architecture (EDA) with a practical focus on Amazon EventBridge, a serverless AWS service used to detect and respond to events in real time. Led by Vimal Daga, the session explains how large-scale platforms like Booking.com, MakeMyTrip, Netflix, and others efficiently manage system-triggered notifications (emails, SMS) using automated event monitoring. This class takes a hands-on approach, using EC2, SNS, and EventBridge to set up workflows that automatically react when server states change—like shutting down or stopping instances.

The session also offers a broader perspective on how automation and serverless services are reshaping the IT industry, reducing the need for manual coding and infrastructure management. You'll also get insights into Devon AI, an emerging AGI tool, and the necessity of continuous skill upgrading to stay relevant in the fast-evolving tech world.

What You'll Learn:

• Introduction to Amazon EventBridge as the core AWS service for implementing Event-Driven Architectures.
  

• The real-world need for serverless EDA in platforms like e-commerce, travel booking, and video streaming.
  

• Use case: Monitoring critical EC2 instances and triggering alerts if a state change (like shutdown) occurs.
  

• Key EDA components:
  

  • Event (state change)
    

  • Action (triggered notification)
    

  • Triggering service (EventBridge)
    

• Integration of AWS services: EC2 + EventBridge + SNS to build automated alert systems.
  

• Concept of Pub/Sub (Publish–Subscribe) architecture using AWS SNS.
  

• Role of SNS topics and subscriptions in sending notifications via email/SMS.
  

• How to create rules in EventBridge to automatically detect and act on specific events.
  

• The power of AWS’s interconnected services and how they simplify advanced use cases.
  

• Insight into the impact of Devon AI and AGI technologies on developer roles and industry expectations.
  

• Emphasis on upskilling and evolving with emerging tools like serverless computing and AI-powered engineering.
  

By the End of This Session, You Will Be Able To:

• Understand and explain the role of EventBridge in serverless, event-driven AWS architectures.
  

• Set up a fully automated monitoring and alerting system using EC2, EventBridge, and SNS.
  

• Define and configure rules in EventBridge to react to EC2 state changes like stop/terminate.
  

• Use SNS to send real-time notifications to emails or mobile devices.
  

• Recognize how EDA is used by major platforms to ensure scalability, efficiency, and cost-saving.
  

• Realize the need for continuous learning in cloud and AI technologies to remain industry-relevant.
  

Build scalable, reactive systems using a fully serverless AWS approach.

Course Description:
In this session, learners continue their journey into Event-Driven Architecture (EDA) by implementing a complete real-time monitoring and automation system using AWS EventBridge. Vimal Daga walks you through setting up customized rules to track AWS events (like EC2 state changes) and take automatic action (such as email notifications via SNS). With an emphasis on real industry relevance, this hands-on session demonstrates how to eliminate the need for manual coding using AWS’s serverless capabilities.

By understanding how to create and configure EventBridge rules, learners experience firsthand how modern cloud applications react to infrastructure changes instantly. The session culminates in a full setup where a stopped EC2 instance triggers an SNS alert—all without writing a single line of code, showcasing the power and simplicity of AWS cloud-native services.

What You'll Learn:

• How to create EventBridge rules to detect specific AWS infrastructure events (e.g., EC2 shutdown).
  

• Role of EventBridge buses in routing event data across services.
  

• Use of pattern matching to monitor instance-specific state transitions (like running → stopped).
  

• Practical understanding of how SNS topics and subscriptions deliver email/SMS alerts.
  

• How to combine services: EC2 (event source) + EventBridge (monitor) + SNS (notifier).
  

• Concept of targets in EventBridge: configuring multiple responses like Lambda, SNS, etc.
  

• Visualizing and testing event rule effectiveness using CloudWatch monitoring.
  

• Real-world applications: Use cases in web applications, smart homes, IoT, and e-commerce.
  

• How AWS abstracts the complexity of backend automation using fully serverless architecture.
  

• Understanding rule matching logic and how AWS tracks internal state changes behind the scenes.
  

By the End of This Session, You Will Be Able To:

• Configure a custom EventBridge rule to monitor EC2 state changes without writing code.
  

• Use EventBridge to trigger actions like email alerts via SNS when a defined event occurs.
  

• Recognize how AWS seamlessly tracks all account-level events through EventBridge's default event bus.
  

• Understand the concept of event patterns and targets, and how they work together.
  

• Visualize and validate event triggers using CloudWatch metrics and monitoring dashboards.
  

• Apply the same serverless automation model to advanced real-world projects, such as launching EC2 from API Gateway and monitoring through EventBridge.
  

• Gain confidence in building highly automated, event-responsive systems using AWS-native tools.

Course Description:
In this session, learners are introduced to Amazon S3 (Simple Storage Service), a powerful and widely used object storage service in AWS. Led by Vimal Daga, the session begins with foundational storage concepts and then transitions into how S3 integrates with other AWS services such as Lambda, SNS, and EventBridge. The session is not just about learning S3—it’s about understanding how to use it in real-world scenarios, including serverless workflows and event-driven architectures.

Participants will explore how cloud storage differs from traditional storage, what makes S3 “serverless,” and how to practically use it for storing files persistently. The class emphasizes hands-on usage, such as creating globally unique buckets, uploading files, and understanding how AWS handles underlying infrastructure transparently.

What You'll Learn:

• Basics of data storage: RAM vs. permanent (persistent) storage.
  

• The concept of cloud-managed storage and Storage-as-a-Service.
  

• Why S3 is considered a serverless, fully managed object storage system.
  

• The difference between cloud storage, block storage (EBS), and file storage (EFS).
  

• Deep dive into object storage:
  

  • Files = "Objects"
    

  • Folders = "Buckets"
    

• Hands-on walkthrough of:
  

  • Creating an S3 bucket.
    

  • Bucket naming rules and global uniqueness.
    

  • Uploading files (objects) into a bucket via the AWS console.
    

• Use case comparison with Google Drive and other cloud storage platforms.
  

• Real-world application of object storage in cloud-native systems.
  

• Preparation for integrating S3 with event-driven workflows using Lambda and SNS.
  

By the End of This Session, You Will Be Able To:

• Understand the purpose and architecture of Amazon S3 in the context of modern cloud applications.
  

• Differentiate between object, block, and file storage in AWS and when to use each.
  

• Create and manage S3 buckets, understanding the constraints on naming and regional availability.
  

• Upload and manage files (objects) in AWS S3 via the console.
  

• Recognize how S3 forms the foundation of many serverless, scalable architectures.
  

Begin preparing to integrate S3 with services like Lambda and EventBridge for advanced workflows.

Course Description:
In this session, Vimal Daga builds upon the foundational knowledge of Amazon S3, diving deeper into the sharing and security aspects of cloud storage. You’ll learn how to make your S3 objects publicly accessible through unique URLs and understand why bucket names must be globally unique. This session also introduces the concept of access control using ACL (Access Control Lists) and how to configure public access correctly without compromising security.

The session emphasizes why cloud storage like S3 is preferable over traditional local storage—highlighting data durability, serverless management, and ease of use. With real-life examples and practical steps, learners experience firsthand how to create buckets, upload files, configure public access, and understand the true value of S3's 99.999999999% durability.

What You'll Learn:

• How S3 objects generate globally unique URLs for public sharing.
  

• Why S3 bucket names must be unique across all AWS accounts and regions.
  

• Difference between bucket-level and object-level access.
  

• Quick walkthrough: making objects publicly accessible using ACL (Access Control Lists).
  

• How to disable "block public access" and enable public visibility for specific objects.
  

• Real-world comparison: S3 vs. traditional storage (like hard drives or personal servers).
  

• Understanding data durability and why AWS S3 is trusted globally for high-resilience storage.
  

• Introduction to object ownership and its role in public data access.
  

• Common use cases: Hosting images, documents, or static content publicly via S3 URLs.
  

By the End of This Session, You Will Be Able To:

• Explain the relationship between S3 bucket/object names and URL formation.
  

• Configure S3 buckets and objects for secure public access using ACLs.
  

• Understand the concept of object-level permissions in a cloud storage environment.
  

• Differentiate between S3 and other AWS storage services like EBS and EFS.
  

• Describe the importance of data durability and how S3 achieves 99.999999999% durability.
  

• Recognize why S3 became the flagship service that propelled AWS into global adoption.
  

Use S3 not just as storage, but as a highly reliable, shareable, and serverless storage solution.

Course Description:
In this advanced and highly practical session, Vimal Daga explores the power of integrating AWS S3 with Lambda functions using built-in event notification triggers. Going beyond basic file storage, the session demonstrates how modern, real-world applications like Netflix and content upload platforms automate backend logic using event-driven workflows.

Through step-by-step guidance, learners configure an S3 bucket to detect events (e.g., file uploads) and trigger AWS Lambda to process the data. This includes setting up SNS for notifications and writing minimal Python code for automation. Use cases range from AI-based video captioning and audio transcription to automated format conversion, all driven by the seamless power of serverless event automation.

What You'll Learn:

• How S3 recognizes events like file uploads (PutObject), deletions, or permission changes.
  

• Real-world use cases:
  

  • Uploading images on web apps storing them in S3.
    

  • Netflix storing videos in S3 and processing them with Lambda.
    

• Creating event-based rules in S3 to trigger automatic actions.
  

• Integration walkthrough:
  

  • Set up a Lambda function to run when a file is uploaded.
    

  • Connect S3 to Lambda and SNS for real-time automation and notifications.
    

• Understanding event as a parameter in Lambda functions for dynamic input processing.
  

• Exploring machine learning applications:
  

  • Lambda-triggered AI services for image recognition, audio-to-text, or video format conversion.
    

• Use of CloudWatch to monitor Lambda invocations triggered by S3 events.
  

• Difference between manual and automatic Lambda invocations in a serverless context.
  

• Overview of S3’s built-in trigger support without needing EventBridge.
  

By the End of This Session, You Will Be Able To:

• Configure S3 to automatically trigger AWS Lambda or SNS on specific events.
  

• Build intelligent workflows where S3 uploads launch serverless compute operations.
  

• Use Lambda’s event input to extract and process object metadata.
  

• Apply this knowledge to real-world use cases like file conversion, AI processing, and alert systems.
  

• Visualize Lambda invocations using CloudWatch logs and metrics.
  

• Leverage the event-driven architecture model to eliminate manual effort and enhance responsiveness.
  

• Understand how industry leaders use S3 + Lambda to build scalable, automated cloud systems.

Course Description:
This session continues the AWS journey by diving into a realistic and highly practical project that integrates multiple AWS services to solve a real-world problem—automating speech-to-text conversion for media content, inspired by how Netflix might handle large volumes of video and audio data.

Led by Vimal Daga, the session focuses on how AWS services like S3, Lambda, and Amazon Transcribe work together to build an event-driven architecture. You’ll learn how to automatically convert any uploaded audio file into text using AWS’s machine learning capabilities—without any prior AI/ML expertise.

This use-case based session emphasizes end-to-end cloud integration, showcasing how different services interact to produce real solutions. It's designed for absolute beginners who want to build projects that matter, not just pass exams.

What You'll Learn:

• How Netflix uses AWS Cloud to manage and scale its global video/audio infrastructure.
  

• Deep dive into Amazon S3 as object storage for video/audio files.
  

• Event-driven architecture using S3 triggers to automate workflows.
  

• Introduction to AWS Lambda as a serverless compute engine to respond to events.
  

• Writing Python code in Lambda using Boto3 to control other AWS services.
  

• Introduction to Amazon Transcribe – AWS's AI-powered speech recognition service.
  

  • How to create transcription jobs.
    

  • Real-time vs. offline transcription.
    

  • Transcribe's role in subtitle generation and video accessibility.
    

• Step-by-step integration of S3 + Lambda + Transcribe to build a fully automated transcription pipeline.
  

• Managing input and output buckets for audio files and transcription results.
  

• Understanding IAM roles, permissions, and security in AWS.
  

• JSON-based transcript output and practical use of that data.
  

• Using AWS for real AI applications without needing to learn machine learning theory.
  

By the End of This Session, You Will Be Able To:

• Set up an end-to-end automated AWS project triggered by file uploads.
  

• Use S3 events to initiate Lambda functions.
  

• Programmatically invoke Amazon Transcribe from Lambda using Boto3.
  

• Store and retrieve transcription outputs in S3.
  

• Understand the fundamentals of integrating AWS services for AI-based automation.
  

• Explain how real companies (like Netflix) use AWS to automate and scale operations.
  

• Add a real-world, multi-service AWS project to your portfolio.

This hands-on AWS session focuses on automating workflows using AWS S3, Lambda, and Transcribe, inspired by real-world scenarios like Netflix's media processing pipeline. In this project-based class led by Vimal Daga, you'll learn how to build a fully functional cloud automation pipeline where uploading an audio file to an S3 bucket triggers a Lambda function that calls AWS Transcribe to convert speech to text.

The session emphasizes event-driven architecture and practical implementation, teaching not just how services work, but how to combine them into production-ready systems. You'll understand the significance of automation, serverless computing, and how to extract metadata from event payloads to dynamically handle incoming data.

What You'll Learn:

• Understanding manual vs. automated AWS workflows.
  

• Automating transcription jobs upon S3 file uploads using Lambda.
  

• Real-time event handling: how S3 triggers Lambda when new files arrive.
  

• Introduction to event-driven architecture using AWS services.
  

• Connecting S3 with Lambda for seamless file-based automation.
  

• Creating and deploying Lambda functions using Python.
  

• How S3 events send data (event object) to Lambda functions.
  

• Parsing event data in Lambda to extract:
  

  • Bucket name
    

  • File (object) name
    

  • Region
    

• Dynamically generating S3 URLs for input to AWS Transcribe.
  

• Invoking AWS Transcribe programmatically using Boto3 (Python SDK).
  

• Best practices for handling multiple, dynamically named audio files.
  

• Troubleshooting triggers and validating AWS CloudWatch logs.
  

• Using CloudWatch to monitor Lambda execution and debug outputs.
  

• Industry tip: Importance of knowing the "what to do" over "how to code".
  

By the End of This Session, You Will Be Able To:

• Build a complete, automated AWS pipeline for audio-to-text conversion.
  

• Configure S3 bucket event rules to trigger Lambda functions.
  

• Write or understand Python code to parse incoming event data in Lambda.
  

• Extract object metadata dynamically to handle file-based processing.
  

• Construct full S3 URLs and integrate with AWS Transcribe via Boto3.
  

• Understand how AWS services communicate and pass data.
  

• Monitor and debug serverless applications using CloudWatch Logs.
  

• Recognize how serverless and event-based architectures apply to real use cases.
  

• Apply the knowledge in industry scenarios like media processing, AI data pipelines, and content automation.
  

• Walk away with a deployable project that's relevant in modern cloud-native businesses.

In this continuation of the AWS automation series, Vimal Daga guides learners through the next phase of building a real-world serverless solution—automatically transcribing audio files uploaded to Amazon S3 using AWS Lambda and Amazon Transcribe.

This hands-on session builds on earlier concepts by diving deeper into dynamic event handling. You'll learn how Lambda can extract metadata from the incoming event payload, construct the S3 file URL on the fly, and use the Boto3 SDK in Python to invoke Transcribe jobs. The focus is on pure automation and cloud-native architecture—ideal for anyone looking to design intelligent pipelines for voice data, customer support automation, or AI training workflows.

What You'll Learn:

• How Lambda functions dynamically detect uploaded file names and bucket locations from event data.
  

• Building real-time S3 → Lambda → Transcribe pipelines.
  

• Using the event variable in Lambda to extract metadata like bucket name and object key.
  

• Constructing full S3 URLs dynamically in Python.
  

• Connecting to AWS Transcribe using the Boto3 library inside Lambda.
  

• Using AWS credentials (access key, secret key, region) securely to authenticate services.
  

• Programmatically starting transcription jobs using start_transcription_job from Boto3.
  

• Understanding required parameters: job name, language code, media format, and media URL.
  

• Managing dynamic content: how to handle multiple files with different names and formats.
  

• Validating Lambda output via AWS CloudWatch logs.
  

• Accessing the transcribed result stored in AWS automatically.
  

• How to refer to official AWS Boto3 documentation for working with services.
  

• Gaining hands-on exposure to integrating multiple AWS services programmatically.
  

By the End of This Session, You Will Be Able To:

• Write Lambda functions that automatically start transcription jobs based on real-time S3 events.
  

• Parse AWS event payloads effectively to extract file and bucket names.
  

• Build dynamic, intelligent AWS Lambda functions that construct S3 URLs at runtime.
  

• Use Boto3 in Lambda for cross-service communication with AWS Transcribe.
  

• Configure and launch Transcribe jobs with custom job names, file formats, and languages.
  

• Debug and monitor serverless functions using AWS CloudWatch Logs.
  

• Automate audio-to-text workflows suitable for customer service, subtitles, AI datasets, and more.
  

• Walk away with a deployable, production-like AWS project using Python, S3, Lambda, and Transcribe.
  

Take one step closer to becoming an industry-ready AWS Cloud Engineer, not just a certified professional.

This session takes AWS automation to the next level by implementing a fully serverless and dynamic audio transcription system using Amazon S3, Lambda, and Transcribe. Led by Vimal Daga, the training focuses on how to automate both input and output workflows using real-world engineering practices. You’ll learn to handle not just file uploads and transcription triggers, but also how to dynamically generate unique job names and output file names—making the system robust, reusable, and production-ready.

The course simulates a real-world pipeline like Netflix might use—processing thousands of audio files automatically, with intelligent job tracking and error management. By the end of the session, learners will understand how to seamlessly integrate multiple AWS services and avoid common pitfalls like job ID conflicts and malformed URLs.

What You'll Learn:

• Defining output locations and formats for AWS Transcribe job results.
  

• Why separate S3 buckets for input and output are best practice.
  

• Dynamically constructing output filenames to avoid overwrites.
  

• Deploying Lambda functions that trigger on S3 put events.
  

• Monitoring Lambda logs in CloudWatch to identify and debug errors.
  

• Troubleshooting common issues such as malformed URLs or special characters in filenames.
  

• Adjusting Lambda timeout settings for long-running jobs.
  

• Handling errors like duplicate job names in AWS Transcribe.
  

• Generating unique transcription job names using Python's uuid module.
  

• Creating unique output file names to avoid collisions during mass uploads.
  

• Real-time validation that files are processed and output is stored successfully.
  

• How to manually run and test the same code locally in case of Lambda errors.
  

• Best practices for handling dynamic data and making your Lambda function scalable.
  

By the End of This Session, You Will Be Able To:

• Configure AWS Transcribe to store outputs in a specific S3 bucket and path.
  

• Automate audio-to-text transcription from upload to result delivery—end to end.
  

• Write Python code to dynamically create unique job names and filenames.
  

• Monitor, test, and debug AWS Lambda executions using CloudWatch logs.
  

• Resolve file naming issues caused by special characters or duplicate entries.
  

• Understand how to use UUIDs and timestamps to maintain system stability at scale.
  

• Extend your project to support thousands of audio files without manual changes.
  

• Design a real-world, scalable cloud application that integrates multiple AWS services.
  

• Gain confidence to build production-ready, serverless pipelines for media, AI, customer service, and more.

In this session, Vimal Daga sets the stage for both new and continuing learners by introducing foundational concepts in cloud computing and comparing AWS with Microsoft Azure. Designed to be a zero-prerequisite class, it welcomes learners new to cloud as well as those pursuing multi-cloud and hybrid cloud strategies.
The session transitions into a detailed real-world enterprise architecture scenario, illustrating how cloud platforms like AWS and Azure are used in large-scale applications. You'll also receive an overview of various cloud services and their real-time relevance across different industries.

What You'll Learn:

• What cloud computing is and how it compares to on-premises setups.
  

• Core infrastructure requirements: OS, RAM, CPU, storage, and how they're provided via cloud.
  

• Public vs Private cloud: AWS, Azure, OpenStack, and data center basics.
  

• Service models in cloud (IaaS, PaaS, SaaS) explained in simple terms.
  

• Real-world use cases: how companies like Netflix use AWS.
  

• Pay-as-you-go pricing model and operational cost benefits.
  

• Quick service comparison: EC2 (AWS) vs Virtual Machines (Azure), SageMaker vs Cognitive Services.
  

• Architectural design and flow of enterprise cloud deployment.
  

• Multi-cloud and hybrid cloud concepts introduced for industry scenarios.
  

• How AWS and Azure differ in service names, usability, and integration.
  

By the End of This Session, You Will Be Able To:

• Understand the fundamental principles of cloud computing.
  

• Differentiate between public, private, and hybrid cloud platforms.
  

• Identify major AWS and Azure services and their real-world applications.
  

• Recognize the role of cloud in enterprise IT infrastructure.
  

• Grasp multi-cloud strategies and why companies adopt them.
  

• Relate cloud concepts to practical architecture designs.
  

• Set a strong foundation for future training in AWS, Azure, or hybrid cloud.

This session by Vimal Daga dives deeper into the practical differences between AWS and Microsoft Azure, focusing on real-world architectural decisions influenced by factors like pricing, compute requirements, and global data center availability. Through comparative examples involving companies like Netflix and McDonald’s, you'll understand how organizations choose between cloud providers—or integrate both—to optimize cost and performance.
The session introduces multi-cloud strategy as a growing necessity and explains how diverse infrastructure needs (e.g., Linux vs Windows servers) lead companies toward adopting services from multiple providers. You’ll also learn about region-based performance optimization, cost-saving strategies, and the business and even political factors affecting cloud adoption.

What You'll Learn:

• Service name differences: EC2 (AWS) vs Virtual Machine (Azure).
  

• Cost comparison: AWS vs Azure, especially for Windows-based workloads.
  

• Real-world example: How Linux World or Netflix chooses between AWS and Azure.
  

• When Azure can be 5x cheaper than AWS for certain services.
  

• The essence of multi-cloud: running different workloads on different platforms.
  

• Business motivations for hybrid and multi-cloud adoption.
  

• Why companies adopt region-specific cloud resources to reduce latency.
  

• Impact of data center availability (regions/locations) on service speed.
  

• The concept of infrastructure as a service (IaaS) and what it includes.
  

• Global coverage comparison: 30 AWS regions vs 60+ Azure locations.
  

• Examples of real-world migrations (e.g., Air India to Azure).
  

• Strategic factors in enterprise cloud decisions (cost, latency, politics).
  

• Importance of cross-cloud expertise for architects and DevOps engineers.
  

By the End of This Session, You Will Be Able To:

• Compare AWS and Azure services for compute, cost, and performance.
  

• Choose cloud platforms based on project-specific operating system needs.
  

• Understand why companies shift toward multi-cloud and hybrid strategies.
  

• Explain the role of data center distribution in reducing latency.
  

• Identify opportunities for cost reduction through intelligent cloud selection.
  

• Analyze global trends in cloud migration from technical and strategic angles.
  

• Position yourself as a multi-cloud architect with a high-demand skill set.
  

• Recognize the business, technical, and political dynamics of cloud adoption.

In this session, Vimal Daga builds a comprehensive real-world architecture for a platform like Netflix, demonstrating how cloud components from AWS and Azure come together to support scalable, high-performance systems.
Learners are introduced to system design fundamentals and how critical services—like compute, storage, scaling, and load balancing—are implemented in both clouds. With a focus on architectural thinking, the session compares services across AWS and Azure while explaining their role in handling user load, latency, and cost optimization.

What You'll Learn:

• System design blueprint of a Netflix-like cloud architecture.
  

• AWS vs Azure services comparison for compute and storage needs.
  

• EC2 (AWS) vs Virtual Machine (Azure) as foundational compute services.
  

• EBS (AWS) vs Azure Disk Storage for scalable, attachable storage.
  

• Understanding auto-scaling: AWS ASG vs Azure Scale Set.
  

• Real-time handling of user traffic using horizontal scaling.
  

• Load balancing across multiple instances: AWS ELB vs Azure Load Balancer.
  

• Concept of stateless servers and dynamic client request handling.
  

• Importance of centralized entry points in distributed systems.
  

• How latency and cost impact design decisions in high-traffic platforms.
  

• Why most enterprises use nearly all major cloud services in projects.
  

• Preview of deep-dive sessions on each cloud service in future classes.
  

By the End of This Session, You Will Be Able To:

• Design scalable, real-world system architectures like Netflix.
  

• Map cloud services across AWS and Azure for similar use cases.
  

• Understand core services required for running large web apps.
  

• Explain concepts like horizontal scaling and auto-scaling automation.
  

• Choose appropriate load balancing strategies for high availability.
  

• Analyze the practical reasons behind service selection in projects.
  

• Prepare to go deeper into each AWS and Azure service in future sessions.
  

• Begin thinking like a cloud architect by visualizing complete workflows.

In this advanced architecture session, Vimal Daga dives deeper into cloud infrastructure by layering DNS, databases, object storage, and event-driven systems onto the previously discussed Netflix-like architecture. Through detailed real-world use cases—from user login and video storage to live event processing and recommendation systems—this session reveals how major companies implement scalable, intelligent services using AWS and Azure.
You’ll gain insight into service names, roles, and practical differences between the clouds, including pricing, performance, and use-case-specific decisions like SQL server placement, media processing, and clickstream analysis.

What You'll Learn:

• Role of DNS in routing: Route 53 (AWS) vs Azure DNS.
  

• Importance of domain name resolution in client-server communication.
  

• How and where Netflix-like apps store user data: RDS (AWS) vs Azure SQL.
  

• NoSQL overview: DynamoDB (AWS) vs CosmosDB and others in Azure.
  

• Use cases for storing media: S3 (AWS) vs Azure Blob Storage.
  

• Automating video conversion: EventBridge + Lambda (AWS) vs Event Grid + Functions (Azure).
  

• Using transcoding/media services: AWS Elastic Transcoder vs Azure Media Services.
  

• Introduction to event-driven architecture and its real-world impact.
  

• Real-time client interaction examples like video quality conversion.
  

• Clickstream analytics: Kinesis (AWS) vs Event Hub (Azure).
  

• Service-specific recommendations for IoT, machine learning, and gaming.
  

• Strategic cloud decisions based on pricing, ownership, and performance.
  

By the End of This Session, You Will Be Able To:

• Implement DNS resolution and domain management using cloud services.
  

• Choose between SQL and NoSQL databases based on data type and usage.
  

• Build scalable object storage systems for files, videos, and images.
  

• Automate backend workflows using serverless functions and event triggers.
  

• Compare AWS and Azure services based on cost, performance, and use case.
  

• Use cloud-native tools for media transcoding and adaptive streaming.
  

• Understand how event-driven systems enable real-time recommendations.
  

• Apply clickstream and IoT data for smarter cloud-based user experiences.
  

• Decide when to adopt multi-cloud to achieve performance and cost goals.

In this session, Vimal Daga explores how cloud platforms integrate AI, machine learning, big data analytics, and business intelligence (BI) tools into real-world applications. You’ll learn how services like SageMaker (AWS) and Azure ML are used to drive recommendations, as well as how BI dashboards (e.g., AWS QuickSight and Azure Synapse/Power BI) help stakeholders visualize insights and make decisions.
This session also introduces the foundational idea of hybrid multi-cloud—combining AWS, Azure, OpenStack, and Terraform to deliver flexible, cost-effective, production-ready architectures.

What You'll Learn:

• Introduction to AI/ML services: SageMaker (AWS) and Azure ML.
  

• Real-time behavior analytics using event streams and clickstream data.
  

• Big data analytics: AWS EMR vs Azure HDInsight for large-scale data processing.
  

• Role of BI tools: AWS QuickSight vs Azure Power BI/Synapse Analytics.
  

• How to visualize data for business decisions using modern BI platforms.
  

• Use-case-based cloud service selection for optimized cost and performance.
  

• Hybrid architecture: using private + multiple public clouds in one system.
  

• Overview of Terraform for infrastructure automation across clouds.
  

• When and why enterprises adopt multi-cloud and hybrid-cloud models.
  

• Use of OpenStack for on-premises private cloud setups.
  

• Concept of abstraction layers in cloud (what cloud providers actually do).
  

• Practical motivation for learning hybrid multicloud strategy.
  

By the End of This Session, You Will Be Able To:

• Use AWS and Azure AI tools for training and deploying ML models.
  

• Select appropriate services for big data analytics based on your use case.
  

• Design business dashboards with powerful cloud-native BI tools.
  

• Identify cost-effective strategies using hybrid or multi-cloud deployments.
  

• Understand real-world examples of hybrid cloud (e.g., banking use cases).
  

• Automate resource provisioning using Terraform across AWS & Azure.
  

• Differentiate between on-prem, public, and hybrid cloud environments.
  

• Grasp the full-stack scope of a modern cloud architect’s responsibilities.

In this session, Vimal Daga introduces the AWS Command Line Interface (CLI) as a powerful tool for cloud administrators and DevOps professionals who want to manage AWS services without relying on the web console or writing full-fledged code.
Designed especially for operations teams, this session covers how CLI bridges the gap between GUI and SDK-based automation. You’ll learn how to interact with AWS services directly from your terminal, create repeatable command structures, and build scripts to automate tasks such as EC2 instance launches, S3 bucket creation, and Lambda function execution.

What You'll Learn:

• Three main ways to interact with AWS: Console (GUI), SDK/API, and CLI.
  

• Benefits of CLI for admins over GUI (manual) and SDK (programmatic) methods.
  

• Installing and configuring AWS CLI on Windows, Linux, or macOS.
  

• Launching EC2 instances directly from the terminal.
  

• Creating and managing S3 buckets using command-line instructions.
  

• Executing Lambda functions and other AWS services via CLI.
  

• How to structure large commands without memorizing syntax.
  

• Writing reusable command templates and modifying them for new use cases.
  

• Automating tasks by organizing CLI commands into shell or batch scripts.
  

• Understanding the flow: single command → script → complete automation.
  

• CLI as a bridge to DevOps for non-programmers and cloud admins.
  

By the End of This Session, You Will Be Able To:

• Configure AWS CLI on your system to securely access AWS resources.
  

• Use CLI to perform tasks like launching EC2, managing storage, and more.
  

• Avoid repetitive GUI steps by automating with terminal-based workflows.
  

• Create, test, and modify your own AWS CLI commands based on requirements.
  

• Combine CLI commands into scripts for repeatable, automated execution.
  

• Understand where CLI fits into the larger DevOps and automation ecosystem.
  

• Take your first steps toward scripting-based AWS infrastructure management.

This session dives into real-world use of the AWS Command Line Interface (CLI) to manage AWS infrastructure without the web console. You’ll learn how to set up and use AWS CLI from a Windows system to launch an EC2 instance, log in using IAM access keys, and understand key differences between human and programmatic authentication in the cloud.

Vimal Daga walks through configuring the CLI, retrieving and using AMI IDs, instance types, regions, and more to construct commands that reflect real DevOps workflows. The lesson emphasizes why CLI knowledge is critical for advanced cloud automation and corporate scenarios where the AWS console may lack necessary features.

What You'll Learn:

• How to install AWS CLI (v2) on Windows or any OS.
  

• Configure AWS CLI using Access Key and Secret Key.
  

• Understand IAM credentials vs manual username/password login.
  

• Learn default region and output format settings (e.g., JSON).
  

• Control AWS services (like EC2) without the AWS console.
  

• Practical CLI login: how base systems authenticate using IAM keys.
  

• Use the aws configure command for secure and persistent login.
  

• Real-world reasoning for CLI use in automation and advanced scenarios.
  

• Step-by-step: Launch an EC2 instance using only the terminal.
  

• Identify required EC2 launch parameters: AMI ID, instance type, count, etc.
  

• Collect values from the console and use them in CLI syntax.
  

• Build custom AWS CLI commands based on your unique use cases.
  

• Introduction to parsing AWS documentation and generating commands.
  

By the End of This Session, You Will Be Able To:

• Set up and authenticate AWS CLI on your system.
  

• Create and use IAM access keys securely.
  

• Understand how CLI enables cloud automation and scripting.
  

• Launch EC2 instances via CLI using real configurations.
  

• Develop your own AWS CLI commands for various services.
  

• Operate AWS infrastructure from the command line with confidence.
  

• Appreciate CLI’s role in DevOps, scripting, and non-GUI environments.

In this hands-on session, Vimal Daga takes you deeper into AWS CLI by demonstrating how to interact with EC2 using real commands. You’ll learn how to describe and launch EC2 instances entirely through the terminal, exploring the powerful help system that makes memorizing commands unnecessary. The session highlights how AWS CLI supports DevOps automation, scripting, and real-time infrastructure control, all without using the AWS console.

You'll discover how to interpret command syntax (synopsis), understand CLI options, and construct custom commands tailored to your use cases. Whether launching, starting, or describing instances, the approach shared here helps you confidently manage AWS infrastructure and transition into automation and CI/CD pipelines.

What You'll Learn:

• Describe EC2 instances using CLI (describe-instances).
  

• Understand how to interpret CLI help commands and syntax.
  

• Launch EC2 instances using run-instances command with all required options.
  

• Learn the difference between main commands, subcommands, and CLI options.
  

• Explore real EC2 values: instance type, AMI ID, security group, subnet, and key pair.
  

• Use start-instances command to change instance states from terminal.
  

• Fetch instance IDs and details programmatically via CLI.
  

• Construct complex commands using AWS documentation and help features.
  

• Importance of aws configure for setting default region and storing IAM keys.
  

• Create repeatable workflows using scripts or integrate CLI commands into Jenkins.
  

• Automate cloud operations and reduce dependency on AWS web console.
  

By the End of This Session, You Will Be Able To:

• Confidently use AWS CLI to describe, launch, and manage EC2 instances.
  

• Build AWS CLI commands based on real-world requirements.
  

• Use AWS help system to find commands and syntax without memorization.
  

• Understand command structure: service → subcommand → options.
  

• Launch custom EC2 instances using AMI ID, key pairs, security groups, etc.
  

• Start and stop EC2 instances from terminal with instance ID.
  

• Automate tasks and trigger CLI commands via DevOps tools or scripts.
  

• Strengthen your command-line skills for production and interview readiness.

In this advanced AWS CLI session, Vimal Daga explores powerful automation techniques for managing cloud resources directly from the command line. You’ll learn how to build and execute custom commands to launch EC2 instances, upload files to S3, and create full cloud projects through reusable scripts. The focus shifts from manual setup to scalable automation suited for real DevOps workflows and collaboration.

Discover how to convert project setups into sharable scripts that can replicate infrastructure across teams or environments. This includes batch uploading media files to S3 (ideal for cases like Netflix-style audio transcription projects) and integrating CLI into CI/CD pipelines. Vimal also shows how to fetch or construct CLI commands using help options and even from within the AWS console UI.

What You'll Learn:

• How to build custom multi-line AWS CLI commands based on specific project needs.
  

• Why every AWS service and region may have different AMI IDs and how to resolve issues.
  

• How to script and automate full cloud projects using command sequences.
  

• Use aws s3 cp to upload files or entire folders to S3 buckets via CLI.
  

• Automate trigger-based workflows like S3 → Lambda → Transcribe for audio-to-text.
  

• Convert manual AWS setups into repeatable CLI scripts for sharing with teams.
  

• Understand CLI command structure: service, subcommand, options, and arguments.
  

• Use AWS console’s "Review Command/API" to extract pre-built CLI snippets (when available).
  

• Upload audio/video files to S3 using filters (include/exclude) and wildcard patterns.
  

• Launch and manage EC2, S3, Lambda, and Transcribe resources entirely from the terminal.
  

• View instance data using describe-instances and start/stop actions using start-instances.
  

By the End of This Session, You Will Be Able To:

• Build and execute advanced AWS CLI commands for EC2, S3, and Lambda.
  

• Automate repetitive AWS tasks using script files tailored to real-world projects.
  

• Upload and organize large media files to S3 buckets programmatically.
  

• Trigger end-to-end workflows (S3 upload → Lambda → Transcribe) via CLI.
  

• Create project templates using CLI for fast infrastructure setup in other AWS accounts.
  

• Replace console-based manual actions with CLI-driven automation for speed and scalability.
  

• Integrate AWS CLI with CI/CD tools like Jenkins and shell scripting.
  

• Gain confidence in managing cloud resources as a DevOps professional.

In this session, Vimal Daga demonstrates how to fully automate the process of uploading files to Amazon S3 using AWS CLI, triggering Lambda functions, and integrating with services like AWS Transcribe. This setup creates a real-world use case similar to automated audio-to-text pipelines for media companies. You’ll also understand how these command-line tools can be paired with DevOps tools like Jenkins to build production-ready cloud operations.

By using commands instead of the AWS console, this session emphasizes scalable project deployment, CI/CD readiness, and the foundation for hybrid/multi-cloud strategies. You’ll also receive insights on upcoming Terraform training and the broader Cloud + DevOps skill set demanded by industry.

What You'll Learn:

• Use aws s3 cp and sync for automated file uploads to S3 buckets.
  

• Trigger Lambda functions from S3 uploads for real-time processing.
  

• Build audio-to-text pipelines using S3 + Lambda + AWS Transcribe.
  

• Learn how CLI commands support broader DevOps strategies.
  

• Automate upload jobs using Jenkins or other CI/CD tools.
  

• Handle bulk uploads with recursive folder copy and include/exclude filters.
  

• Convert any AWS manual workflow into scripts using CLI.
  

• Understand how CLI commands make multi-cloud and hybrid strategies replicable.
  

• Benefits of scripting vs manual setup for large-scale project sharing.
  

• AWS CLI as the backbone for integrating cloud tools in automation projects.
  

• How to join Terraform weekend training for infrastructure as code (IaC).
  

• Recap: Why knowing command line + automation + integration = CloudOps expertise.
  

By the End of This Session, You Will Be Able To:

• Upload files or folders to S3 directly from CLI, bypassing the AWS console.
  

• Trigger Lambda functions and downstream services automatically via S3.
  

• Integrate AWS CLI commands into DevOps pipelines using Jenkins or scripts.
  

• Write and customize AWS CLI commands confidently based on real use cases.
  

• Prepare for infrastructure automation using tools like Terraform.
  

• Understand and build end-to-end automated solutions in cloud environments.
  

• Position yourself for advanced DevOps or CloudOps roles with real project workflows.
  

• Move from basic cloud learning to hands-on, production-grade automation.

This session introduces AWS Platform as a Service (PaaS) with a focus on Elastic Beanstalk, comparing it to traditional Infrastructure as a Service (IaaS) through EC2. Led by Vimal Daga, the training explains the layered responsibility model in cloud services and guides learners in making smart choices between managing their own infrastructure versus leveraging ready-made platforms for faster deployment.

Through real-world use cases like Netflix's infrastructure decisions, the session builds a strong foundation on how industry players decide between configuration-heavy EC2 instances and managed solutions like Elastic Beanstalk for web application hosting. This session includes practical demos, comparisons, and an in-depth understanding of deployment approaches, especially useful for developers and DevOps beginners.

What You'll Learn:

• The concept of Platform as a Service (PaaS) and how it differs from Infrastructure as a Service (IaaS).
  

• Deep understanding of EC2 instances and what AWS provides in terms of responsibility (hardware + OS) and what the user is responsible for (configuration, runtime, web/app server).
  

• Detailed explanation of deployment complexity in EC2 including installation of web servers, programming runtimes (PHP, Python), and application configurations.
  

• How Elastic Beanstalk simplifies deployment by providing a pre-configured platform (hardware + OS + web server + runtime) where developers only need to deploy their code.
  

• Comparison of Netflix’s use of EC2 for custom configurations vs startups or smaller teams using Beanstalk for rapid deployment without admin overhead.
  

• Industry equivalent services: Google App Engine (GCP), Azure App Service (Microsoft Azure).
  

• Demo: Launching an EC2 instance, setting up a web server, deploying a PHP file manually to understand the configuration-heavy process.
  

• Introduction to Elastic Beanstalk UI and simplified deployment steps.
  

By the End of This Session, You Will Be Able To:

• Clearly differentiate between EC2 (IaaS) and Elastic Beanstalk (PaaS) in terms of configuration effort, flexibility, and industry use cases.
  

• Deploy a basic web application manually on EC2, understanding each configuration step.
  

• Understand when and why to choose Elastic Beanstalk over EC2 depending on team size, infrastructure needs, and deployment goals.
  

• Recognize the benefits of PaaS in reducing time-to-market and administrative overhead.
  

• Understand how modern web applications can leverage AWS PaaS for scalability and reliability.

Continue your AWS journey by exploring Elastic Beanstalk, Amazon’s Platform as a Service (PaaS) offering that simplifies the deployment and management of web applications. In this session led by Vimal Daga, you'll experience the power of deploying PHP-based web applications without needing to handle the low-level configurations of web servers or operating systems. This hands-on training walks you through the differences between IaaS (like EC2) and PaaS (like Beanstalk) and when to use each.

Through real-world analogies and demonstrations (including how logs are captured, environments are managed, and versions are deployed), you’ll learn how developers and teams can use Beanstalk to focus on writing and deploying code rather than managing infrastructure. This is an essential session for anyone aiming to build modern, scalable, and reliable applications in the cloud with minimal overhead.

What You'll Learn:

• How server logs are generated and monitored in Linux-based cloud environments.
  

• Responsibilities in the shared responsibility model: what AWS manages vs. what users manage.
  

• The distinction between IaaS (EC2) and PaaS (Elastic Beanstalk) in terms of system setup, runtime installation, and deployment.
  

• How to deploy a PHP web application using Elastic Beanstalk with minimal configuration.
  

• Overview of web server support (Apache, NGINX, IIS) and runtime environments (PHP, Python, Java, etc.) in Beanstalk.
  

• Elastic Beanstalk environment types (web server vs worker) and their use cases.
  

• Concept of deployment environments (Dev, Test, Prod) and real-world flow: from developer environment to production.
  

• Introduction to domain naming and how Beanstalk assigns default public DNS.
  

• Understanding versioning in deployments and its significance in maintaining and updating applications.
  

• Using Beanstalk's web interface to upload application bundles and deploy them.
  

• Discussion on high availability, load balancing, and how Beanstalk integrates those automatically.
  

• Best practices for deploying code, testing in isolated environments, and preparing for production rollouts.
  

By the End of This Session, You Will Be Able To:

• Confidently differentiate between EC2 and Beanstalk based on configuration complexity and use cases.
  

• Use Elastic Beanstalk to deploy PHP applications without manually configuring runtime or web servers.
  

• Understand and leverage environment naming (Dev, Prod) in deployment strategies.
  

• Upload, deploy, and version-control your applications using the Beanstalk console.
  

• Identify supported runtimes and web servers available in Beanstalk and select the right ones for your application.
  

• Use Beanstalk’s built-in infrastructure (DNS, scaling, high availability) to deploy production-ready apps.
  

Begin implementing modern deployment strategies with awareness of concepts like canary deployment, blue-green deployment, and rolling updates.

Dive deeper into Elastic Beanstalk, Amazon's powerful Platform as a Service (PaaS), by learning how to set up secure and scalable application environments. In this hands-on session, Vimal Daga walks you through configuring roles, key pairs, VPCs, security groups, instance types, and deployment strategies while maintaining real-world relevance and industry-ready skills. You’ll learn how Elastic Beanstalk works under the hood using EC2, how to manage deployment versions, and how teams use multiple environments (Dev, QA, Prod) in modern CI/CD pipelines.

Whether you’re a developer, DevOps enthusiast, or aspiring cloud architect, this session will give you a comprehensive look at how to deploy, maintain, and evolve web applications using AWS best practices and automation through Beanstalk.

What You'll Learn:

• Understanding service roles and key pair configuration in Beanstalk deployment.

• How Elastic Beanstalk leverages EC2 instances, AMIs, and operating systems behind the scenes.

• The role of VPCs, subnets, and availability zones (AZs) when deploying applications.

• Setting up and assigning security groups (firewalls) for public access via HTTP/port 80.

• Handling database requirements with future integration into Amazon RDS.

• Choosing between default and custom networks, and configuring public IP settings.

• Importance of auto scaling and load balancing (ALB/NLB) in production systems.

• Understanding the impact of AMI selection (Amazon-provided vs. custom user-created AMIs).

• Managing health checks, cloud monitoring, and maintenance time windows.

• Using SNS notifications for environment-level alerts and updates.

• Setting up and deploying application versions (v1, v2, etc.) and understanding version lifecycle management.

• Deploying environment-specific platforms for different teams (Dev, QA, Prod) using Beanstalk environments.

• Introduction to deployment strategies like rolling updates, blue-green deployments, and their future coverage in DevOps/Kubernetes sessions.

• Best practices for separating responsibilities between developer code and infrastructure management.

By the End of This Session, You Will Be Able To:

• Configure and deploy a secure web application on Elastic Beanstalk using EC2-backed infrastructure.

• Assign roles, VPCs, and security groups in a Beanstalk deployment pipeline.

• Understand how AWS automates infrastructure tasks while offering control and customization.

• Deploy new versions of your application using Beanstalk's versioning system.

• Distinguish between different deployment environments and configure them appropriately.

• Identify when to use built-in AMIs vs. your own customized AMIs for deployments.

• Plan for real-world maintenance schedules and understand Beanstalk's update workflows.

• Access your live application via a public domain provided by Beanstalk.

• Navigate and utilize the Beanstalk console to edit configurations, monitor health, and manage application versions.

• Prepare for advanced deployment models using Beanstalk, and lay a foundation for integrating Kubernetes and CI/CD in future sessions.

In this follow-up session on Elastic Beanstalk, Vimal Daga takes learners beyond the deployment basics and dives into critical aspects of real-world AWS usage. From managing access via IAM roles to understanding cost implications of PaaS vs IaaS, this session equips learners with the tools and mindset to make informed decisions in a cloud environment. Practical insights on GitLab integration, secure credential handling, and EC2 resource tracking are covered in detail.

This class emphasizes cost-effective deployment, access control strategies, and showcases how to use Elastic Beanstalk while addressing common team-level challenges, such as secret sharing, deployment pipelines, and infrastructure security. Learners are encouraged to showcase their skills via projects and community visibility for better career prospects.

What You'll Learn:

• Cost comparison between Elastic Beanstalk and EC2, and how to use AWS Pricing Calculator for planning.

• How Elastic Beanstalk uses EC2 under the hood and how to access those instances via private key.

• Understanding IAM best practices:

• Creating IAM users with limited permissions.

• Using access keys instead of passwords.

• Intro to STS (Security Token Service), OAuth, and SSO integrations.

• Security group limitations and VPC-level configurations for production-grade deployments.

• Introduction to AWS Amplify as a full-stack development platform and how it compares with Elastic Beanstalk.

• Best practices for project visibility, including showcasing tasks, deployments, and real-world projects on LinkedIn.

• The importance of consistency and quality in sharing your work to get job attention.

• Career advice: How the job market identifies talent based on real-world output, not just certifications.

• Mindset shift: From passive learners to visible cloud practitioners through content-driven learning.

• Understanding why Beanstalk is preferred in some scenarios despite its higher cost compared to EC2.

• How to monitor instances launched via Beanstalk and how to log in to inspect configurations.

• Encouragement to build hybrid skills (e.g., DevOps + Cloud + Full-Stack) for better employability.

By the End of This Session, You Will Be Able To:

• Use IAM roles and keys securely to enable collaboration without compromising root credentials.

• Calculate and compare deployment costs between Beanstalk and EC2 using AWS tools.

• Access and monitor Beanstalk-launched EC2 instances to validate platform setup.

• Plan for future integration with GitLab and implement secure DevOps workflows.

• Understand the role of Amplify in full-stack development vs Beanstalk’s focus on app deployment.

• Showcase your learning and projects professionally on platforms like LinkedIn to attract recruiters.

• Recognize the importance of industry-focused visibility for career acceleration.

• Prepare your profile and presence to be more appealing for real-world job opportunities.

• Leverage practical knowledge gained through training to build a high-value, job-ready portfolio.

In this insightful session, Vimal Daga introduces learners to secure cloud automation by integrating Python (Boto3), EC2, and IAM roles in AWS. The focus is not just on writing automation code, but also on implementing secure best practices around credential handling, role-based access, and controlled infrastructure management.

Through the session, learners understand the three core ways to interact with AWS—Console (UI), Command Line Interface (CLI), and Application Programming Interface (API)—and the risks of hardcoding credentials. The session culminates in a real-world project, where an EC2 instance is used to securely automate AWS services using IAM roles, without exposing secret keys.

This session highlights industry-aligned automation practices, secure identity and access control, and real-time EC2 interaction with Python code—making it an essential experience for anyone pursuing AWS automation, DevOps, or backend engineering roles.

What You'll Learn:

• Different methods to interact with AWS: Console, CLI, and API.

• How to write Python code using Boto3 to automate AWS services.

• Risks of hardcoding access keys inside scripts and secure alternatives.

• Using aws configure to safely store credentials in local OS environments.

• How Python scripts and CLI commands retrieve credentials from the system.

• Launching and managing EC2 instances from Python scripts.

• Executing AWS automation code directly from EC2 instances.

• Installing necessary Python libraries (like boto3) and environment setup on EC2.

• Understanding the use of IAM roles for secure EC2 communication with other AWS services.

• Creating IAM roles to grant fine-grained access to EC2 instances.

• Real-world use case: Setting up an EC2 machine for internal AWS service automation without sharing credentials.

• Understanding instance-level permissions to control developer actions.

• Comparison of credential-based and role-based access control in cloud environments.

• Planning secure project execution pipelines using IAM and Boto3.

By the End of This Session, You Will Be Able To:

• Confidently write and execute Python scripts using Boto3 to manage AWS services.

• Avoid the practice of embedding credentials inside code by using proper credential storage.

• Set up and configure aws cli to securely interact with AWS from your laptop or EC2 instance.

• Deploy EC2 instances specifically for internal cloud service management.

• Assign IAM roles to EC2 to restrict or allow access to specific AWS services like S3, EC2, etc.

• Understand and apply the principle of least privilege using IAM roles.

• Establish secure developer workflows where code runs only from permitted machines (e.g., EC2) and not elsewhere.

• Begin automating AWS infrastructure the way it's done in the industry—securely, modularly, and at scale.

• Lay the foundation for deeper cloud automation practices involving Lambda, S3, and CI/CD integrations.

In this deep-dive session, Vimal Daga focuses on one of the most powerful yet misunderstood features of AWS—IAM Roles. Learners will explore how to securely enable one AWS service (like EC2 or Lambda) to access another service (like S3 or EC2) without embedding access keys or secrets in their code.

The session provides an extensive look at policy-based access control, real-time role creation and attachment, permission testing, and the differences between IAM users vs. IAM roles. Practical examples include enabling EC2 instances and Lambda functions to interact with other AWS services, using least-privilege principles. You’ll also witness how AWS handles implicit and automatic role assignment in certain services and how to extend those capabilities for custom use cases.

What You'll Learn:

• Understanding the difference between IAM users and IAM roles in AWS.

• Why and when to use IAM roles over hardcoded credentials or IAM users.

• How to create a custom IAM role and assign it to EC2 or Lambda securely.

• Attaching permissions to IAM roles: full access, read-only, and custom policy setups.

• Real-time demo: assigning an S3 read-only policy to an EC2 instance and restricting upload capability.

• How roles enable secure automation workflows without exposing access keys.

• Step-by-step process of modifying EC2 instance roles after launch.

• Role-based security in Lambda functions for interacting with EC2 or S3.

• Understanding AWS’ built-in behavior of auto-attaching roles in integrations like Lambda → CloudWatch.

• Creating multiple permissions within a single role and testing actions like ec2:RunInstances and s3:PutObject.

• Limitations of IAM roles (e.g., one-way access and explicit scope of permissions).

• Using roles in production to ensure developers can access only what they need, only from designated environments.

• Full walkthrough of how IAM roles underpin microservice-to-microservice communication in the AWS ecosystem.

By the End of This Session, You Will Be Able To:

• Create and manage IAM roles to enable AWS service integrations.

• Attach roles to EC2 and Lambda to safely replace access key usage.

• Restrict or allow access to services like S3, EC2, CloudWatch based on principle of least privilege.

• Understand when to create custom policies vs. using AWS managed policies.

• Modify existing roles and policies dynamically based on project needs.

• Explain and implement secure service-to-service communication in cloud-native architectures.

• Use IAM roles to secure your CI/CD workflows, automation scripts, and serverless applications.

• Detect and troubleshoot permission errors by analyzing IAM role configurations.

• Avoid common mistakes in identity and access control through practical awareness and demos.

Design AWS environments that prioritize security, scalability, and operational control through proper role-based access management.

In this session, Vimal Daga introduces a powerful AWS service designed for centralized cloud management—AWS Systems Manager, with a focus on the Run Command feature. The session begins by exploring the typical challenges associated with managing and configuring multiple EC2 instances manually. As organizations scale, configuring hundreds or thousands of servers one by one becomes inefficient and error-prone.

This training presents AWS Systems Manager as a centralized, secure way to execute administrative tasks, perform routine updates, and configure systems across multiple EC2 instances without direct SSH access. Through a real-time hands-on demo, learners automate the process of converting EC2 instances into functional web servers using simple shell commands—all managed from one interface.

This session demonstrates how cloud administrators can orchestrate configuration, maintenance, and deployment tasks across fleets of instances using secure, scalable, and automated practices that are vital for DevOps and cloud operations teams.

What You'll Learn:

• What AWS Systems Manager is and how it enables centralized resource management.

• Understanding EC2 instance configuration workflows and associated operational challenges.

• Why manual configuration at scale is inefficient and introduces operational risks.

• The concept of configuration management and how it applies to real-world OS-level tasks.

• Introduction to Systems Manager Run Command, and how it replaces manual SSH access.

• How to write and execute scripts (called Documents) for EC2 configuration using shell scripting.

• How to install and configure web servers (like Apache) remotely using Run Command.

• Difference between one-time configuration and repeated operational tasks (like patching, backup).

• Steps to run remote commands across multiple EC2 instances simultaneously.

• Understanding how scripts become automation documents, allowing commands to be run across regions.

• Security considerations: No need to store SSH keys or open ports—Run Command uses IAM-based access.

• Use cases for Systems Manager beyond EC2: managing on-premise servers, hybrid cloud, and other providers.

• Real-world example: launching two EC2 instances and remotely turning them into web servers via Systems Manager.

By the End of This Session, You Will Be Able To:

• Use AWS Systems Manager Run Command to execute scripts remotely across EC2 instances.

• Convert EC2 instances into web servers without logging into them individually.

• Automate repetitive admin/configuration tasks using centralized command execution.

• Understand how automation scripts (shell, PowerShell, Python, etc.) can be deployed using Systems Manager.

• Eliminate the need for SSH keys and reduce attack surface by leveraging Systems Manager access.

• Build scalable cloud management workflows suitable for DevOps, IT admin, and cloud operations teams.

• Distinguish between Systems Manager and traditional configuration tools, and apply it in multi-instance environments.

• Design and deploy secure, centralized infrastructure maintenance strategies in AWS.

• Start incorporating AWS-native automation techniques into your enterprise projects and training portfolios.

In this advanced hands-on session led by Vimal Daga, dive deep into managing and automating AWS EC2 instances using AWS Systems Manager (SSM), Lambda, and API Gateway. The course walks you through a complete real-world use case of how to register EC2 instances with SSM, understand the role-based access mechanisms, and control infrastructure through serverless automation.

This training session covers troubleshooting when EC2 instances don’t appear in SSM, explains the architecture behind EC2-SSM interaction, and guides you in enabling remote command execution using run commands. You’ll then scale this further by integrating Lambda functions and API Gateway to trigger automation (e.g., patching, backup, web server setup) with a click from a web or mobile frontend.

What You'll Learn:

• Why EC2 instances may not register with SSM and how to fix it.
  

• The role of IAM in connecting EC2 with SSM.
  

• EC2 agent (Amazon SSM Agent) and how it communicates with SSM.
  

• How to view and analyze logs to debug connectivity issues.
  

• Steps to create and attach IAM roles that grant EC2 permission to communicate with SSM.
  

• How to restart SSM agent services manually or via instance reboot.
  

• Use of AWS SSM Run Command to execute scripts and install software remotely.
  

• Parallel configuration of multiple EC2 instances (e.g., Apache web server setup).
  

• Using Lambda to trigger SSM commands automatically.
  

• Creating a REST API with API Gateway to invoke Lambda functions.
  

• End-to-end project demo: pressing a mobile/web button to run SSM scripts via Lambda/API Gateway.
  

• Real-world architecture idea: build a fully remote-controlled EC2 infrastructure via web frontend.
  

By the End of This Session, You Will Be Able To:

• Explain how EC2 and SSM interact and the role of IAM in enabling this.
  

• Configure IAM roles to allow EC2 to register with SSM.
  

• Automate EC2 tasks like backups, installations, and patching using SSM.
  

• Write Lambda functions to trigger SSM commands.
  

• Build an API Gateway endpoint to trigger automation from a web/mobile app.
  

• Set up a mobile/web UI to control EC2 infrastructure via serverless AWS services.
  

• Implement a real-world automation solution suitable for enterprises.
  

• Start building industry-grade DevOps and cloud automation projects with confidence.

Step into the world of secure, scalable user authentication using AWS Cognito! In this session, led by Vimal Daga, you'll learn how AWS Cognito helps developers integrate sign-up, sign-in, and sign-out functionality into applications without writing a single line of backend authentication code. From real-world examples like Facebook and Udemy to complex login flows using social platforms, this course breaks down how AWS Cognito simplifies identity management and federated access.

You’ll explore how Cognito handles account creation, secure login, multi-factor authentication (MFA), social logins (Google, Facebook), and integrates directly with your app’s frontend and backend securely. No need to develop your own user databases or login pages — Cognito provides fully customizable UI pages and secure storage behind the scenes.

This training focuses on real-world challenges in authentication and identity management, especially how to avoid security pitfalls when handling user credentials. It's designed for anyone building applications who wants a robust, industry-grade authentication system with minimal development effort.

What You'll Learn:

• Why every modern application needs sign-up, sign-in, and sign-out flows.
  

• Challenges of building your own authentication: frontend, backend, databases, security.
  

• How AWS Cognito eliminates this complexity using built-in UI and logic.
  

• Cognito user pools: What they are, how they manage users securely.
  

• Social login integration: How to enable login via Google, Facebook, etc.
  

• Concepts of Identity Provider (IdP), Service Provider (SP), and trust relationships.
  

• OAuth and OpenID Connect: The security protocols used under the hood.
  

• Multi-factor authentication (MFA) and advanced user verification flows.
  

• Callback URLs and redirecting users post-login to your custom app/dashboard.
  

• How Cognito stores user attributes securely (e.g., email, phone, DOB).
  

• Best practices for identity federation and real-world identity integration.
  

By the End of This Session, You Will Be Able To:

• Set up a fully functioning authentication flow using AWS Cognito without backend coding.
  

• Enable sign-up, sign-in, and sign-out features in any web or mobile app.
  

• Integrate social login (Google, Facebook) in your application securely.
  

• Understand the architecture of authentication: IdP, SP, OAuth, OpenID, and federated identity.
  

• Use Cognito user pools and attributes to manage users and their data.
  

• Customize the Cognito login UI and redirect users to your own application page.
  

• Ensure your app is secure, scalable, and user-friendly without reinventing the wheel.
  

• Start building enterprise-ready apps with built-in identity and access management.

Step into the practical implementation of user authentication using AWS Cognito. In this session, led by Vimal Daga, you’ll learn how to integrate a secure, scalable sign-up and sign-in flow into your own web application without writing complex backend authentication logic. The session walks through setting up a Linux-based web server on EC2, building a simple HTML login UI, and configuring Cognito to manage users, including multi-factor authentication and social login options.

This course emphasizes real-world application—connecting Cognito with a live EC2-hosted website and handling everything from user creation to callback routing post-login. Whether you're building a web portal, mobile app, or backend service, this training teaches you how to implement cloud-based identity management using AWS Cognito, reducing your security risk and development overhead.

What You'll Learn:

• How AWS Cognito helps developers with pre-built, secure user authentication.

• Create and configure user pools to manage application users.

• Set up a simple web application on EC2 with HTML login pages.

• Understand the login flow:

• Index page → Sign-up/Login (via Cognito) → Callback to app homepage
  

• Customize sign-up fields (email, username, phone) and policies.

• Implement password strength policies for added security.

• Enable and configure multi-factor authentication (MFA) via SMS and Google Authenticator.

• Integrate social logins (Google, Facebook) using Cognito’s federated identities.

• Set up self-service account recovery via email and SMS.

• Use Cognito's built-in UI for user registration and login without coding from scratch.

• Understand federated identity, identity providers (IdP), and service providers (SP).

By the End of This Session, You Will Be Able To:

• Configure AWS Cognito user pools for your application.

• Launch and host a web application on EC2 and link it to Cognito.

• Add sign-up, sign-in, and sign-out flows to your web app without writing backend code.

• Integrate MFA and social logins into your authentication system.

• Understand OAuth and OpenID concepts behind social logins.

• Build a complete authentication flow from login page to secured content delivery.

• Use secure, scalable identity management practices in real-world applications.

• Start building cloud-native apps with enterprise-grade login systems using AWS Cognito.

Explore an advanced real-world implementation of AWS Cognito where user sign-up, sign-in, multi-factor authentication (MFA), and social login are configured step by step with full customization. This session, led by Vimal Daga, walks through how to define user attributes, integrate federated identities (like Google and Facebook), manage message delivery, configure hosted UIs, and build secure trust between your application and Cognito using client secrets.

You’ll set up a secure user pool, define custom sign-up forms (e.g., student ID), integrate MFA, and learn how Cognito uses SNS and SES for communication. You’ll also learn how to link your login flows to real-world applications using HTTPS callback URLs, create secure domain-based login pages, and explore the practical importance of OAuth, OpenID, and identity federation in enterprise setups.

This session is ideal for developers and cloud engineers building applications that need secure, scalable, and customizable login flows powered by AWS Cognito.

What You'll Learn:

• Understand user attributes and how to collect additional custom fields during sign-up (e.g., student ID).

• Create secure login/sign-up flows using AWS Cognito hosted UI.

• Set up SES (Simple Email Service) and SNS (Simple Notification Service) integration for message delivery.

• Configure IAM roles for Cognito to communicate with SNS.

• Enable and customize multi-factor authentication (MFA) using SMS and app-based authenticators.

• Understand federated login using Google and Facebook (OAuth/OpenID-based).

• Establish trust between your app and Cognito via client secrets.

• Set up HTTPS callback URLs for secure login redirection.

• Use app clients to connect your hosted login UI with your backend systems.

• Customize user pools for different roles or application needs.

• Create secure logout redirection URLs (sign-out callback).

• Work with Cognito’s role as an Identity Provider (IdP) and your app as a Service Provider (SP).

• Overview of setting up trusted login flows using OAuth and OpenID Connect.

By the End of This Session, You Will Be Able To:

• Define and manage user attributes and custom fields in Cognito.

• Send verification and MFA messages via SES and SNS.

• Configure hosted Cognito UI with your own domain or AWS-hosted domain.

• Enable sign-up, sign-in, and sign-out redirection using callback URLs.

• Integrate federated identity with social logins (Google/Facebook).

• Create a trust relationship between Cognito and your application using client secrets.

• Secure your application access using AWS Cognito’s authentication framework.

• Implement a login flow from UI to homepage using secure OAuth-based workflows.

• Build scalable and secure user identity layers without managing authentication logic manually.

Conclude your deep dive into AWS Cognito with a complete, real-time implementation of user authentication from start to finish. In this advanced session led by Vimal Daga, you’ll witness the live integration of Cognito’s hosted UI into a web application, the configuration of user sign-up flows, email and SMS verification, and live user creation in Cognito’s user pool. This hands-on session demonstrates how to handle callback URLs, apply custom branding, and leverage OAuth 2.0 behind the scenes for secure login.

You’ll see how users sign up with email, mobile number, and password — followed by multi-factor authentication (MFA) using email or SMS. The session also demonstrates customizing the login UI with your own logo, colors, and links, and securely redirecting authenticated users to your internal app. You'll wrap up the session with an understanding of identity architecture, microservices integration, and practical use cases in the real world.

What You'll Learn:

• Customize the Cognito login/sign-up UI using logos, colors, and CSS.

• Configure Cognito to collect user attributes (email, gender, mobile, student ID).

• Create hosted UI with a custom domain or AWS subdomain.

• Live walkthrough of user registration using Cognito.

• Handle email verification using SES and SMS verification using SNS.

• Understand and use IAM roles for Cognito-SNS communication.

• Manage user pools: view registered and confirmed users.

• Secure integration between your application and Cognito via client secrets.

• Redirect users post-login using secure callback URLs.

• Live demo: Add hosted login page link to your HTML app (index.html).

• Experience real-time user verification via OTP/email.

• Enable OAuth-based trust and authentication flows without code.

• Use Cognito in a real-world application architecture with microservices.

• Overview of advanced integration with API Gateway using Cognito authentication.

By the End of This Session, You Will Be Able To:

• Fully integrate AWS Cognito into a custom web application.

• Create and manage user pools with real-time registration and login tracking.

• Securely redirect users to your internal application post-authentication.

• Collect custom sign-up data fields and verify users via email/SMS.

• Understand the role of IAM in integrating Cognito with other AWS services.

• Design branded sign-up and login pages with your organization’s look and feel.

• Implement OAuth-based login workflows without backend development.

• Control access to applications and APIs using Cognito and API Gateway.

• Apply cloud-native practices to secure authentication in modern applications.

• Prepare for real-world deployment and AWS certification with practical confidence.