AWS Certified Solutions Architect Associate Course 2026

Embark on your journey to mastering Amazon S3 (Simple Storage Service) with this beginner-friendly tutorial! This video provides a blend of theory and hands-on demonstration to help you understand and work with the fundamentals of S3. Here’s what you’ll learn:

• The essential concepts of AWS S3, including its purpose and use cases.

• How to create an S3 bucket from scratch while understanding the importance of a unique bucket name.

• Explanation of tags and their significance for organizing and managing S3 buckets effectively.

• A practical demonstration of uploading a .txt file from your local computer to an S3 bucket to showcase basic storage functionality.

This video is perfect for anyone looking to understand AWS S3 at a foundational level and gain confidence in managing cloud storage.

In this comprehensive tutorial, we delve into the powerful concept of AWS S3 object versioning.

What You'll Learn:

1. Theory Concepts: Understand how versioning helps restore objects and protects against accidental deletions or overwrites.

2. Impact of Disabling Versioning: Learn what happens when S3 versioning is disabled and its implications.

3. Hands-On Demonstration: Follow along as we implement S3 object versioning step-by-step.

Practical Steps Covered:

1. Uploading a .txt File: Upload a text file from your local computer to an S3 bucket.

2. Disabling Versioning: Discover the version ID when versioning is disabled.

3. Enabling Versioning: See the version ID once versioning is enabled.

4. Deleting an Object: Demonstrate how versioning preserves deleted objects.

By the end of this video, you'll gain a solid understanding of AWS S3 object versioning and be equipped to implement it in your own projects. Whether you're a beginner or an experienced cloud professional, this tutorial will enhance your skills.

Welcome to our comprehensive guide on AWS S3 Lifecycle Policies! In this video, we dive deep into the theoretical concepts and practical applications of S3 lifecycle management.

Here's what you'll learn:

S3 Storage Classes Explained:

1. S3 Standard: Understand the default storage class, designed for frequently accessed data.

2. S3 Intelligent-Tiering: Learn how this class automatically moves data between two access tiers when access patterns change.

3. S3 Glacier Deep Archive: Discover the most cost-effective storage for data that is rarely accessed and requires long-term retention.

S3 Lifecycle Policy Diagram:

1. Visualize and grasp the lifecycle policies with the help of detailed diagrams.

2. Learn how to automate the transition of objects between different storage classes based on their age and access patterns.

Importance of S3 Lifecycle Management:

1. Explore why lifecycle management is crucial for optimizing storage costs and maintaining efficient data access.

2. See real-world examples of how businesses benefit from implementing effective lifecycle policies.

Cost Demonstration in AWS Console:

1. Step-by-step guide to calculating the costs of different S3 storage tiers using the AWS Pricing Calculator.

2. Compare the costs and make informed decisions about which storage class to use for your data.

Join us for this in-depth tutorial to master S3 lifecycle policies and manage your AWS storage effectively.

Welcome to our comprehensive hands-on tutorial on AWS S3 lifecycle policy! In this video, we'll guide you through the complete process of setting up and managing lifecycle rules for your Amazon S3 bucket.

What you'll learn:

1. Creating an S3 Bucket: Step-by-step instructions to create a new S3 bucket in your AWS account.

2. Uploading Files to S3: Learn how to upload a .txt file from your local computer to the newly created S3 bucket.

3. Setting Up Lifecycle Rules: Discover how to configure object lifecycle rules to manage data efficiently.

Key Concepts:

1. Creating an S3 Bucket - A detailed walkthrough on creating an S3 bucket in AWS.

2. Uploading Files to S3 Bucket - Demonstrating how to upload a .txt file from your local computer to the S3 bucket.

3. Configuring Object Lifecycle Rules:

a) Transition to S3 Standard-IA: After 35 days, the object will transition from S3 Standard to S3 Standard-IA.

b) Transition to S3 Glacier: After 90 days, the object will move to S3 Glacier for long-term storage.

c) Object Deletion: After 120 days, the object will be automatically deleted.

Practical Demonstration:

1. Creating S3 Bucket

2. Uploading a .txt File from Local Computer to S3 bucket

3. Configuring Object Lifecycle Rules:

4. Transition to S3 Standard-IA after 35 days

5. Move to S3 Glacier after 90 days

6. Delete the object after 120 days

By the end of this video, you'll have a thorough understanding of how to set up and manage S3 lifecycle policies to optimize storage costs and data management.

We will learn the basics of S3 Presigned URL, how it works and what is the advantage of it.

Unlock the power of AWS S3 Pre-Signed URLs in this hands-on, practical course! Whether you're a cloud beginner or an experienced developer, this course will guide you through both the theoretical concepts and real-world implementation of S3 Pre-Signed URLs.

What you'll learn:

1. Understand the fundamental concepts behind AWS S3 Pre-Signed URLs

2. Generate pre-signed URLs for secure access to S3 objects

3. Upload local image files to S3 using the AWS Management Console

4. Perform the same upload process using AWS CloudShell and CLI commands

5. Explore best practices and security considerations

This video is packed with step-by-step demonstrations, making complex AWS concepts easy to understand. By the end, you'll be confidently using pre-signed URLs for controlled, time-limited access to your S3 objects.

Dive into the fundamentals of Amazon Elastic Block Store (EBS) with this beginner-friendly course! Learn how EBS volumes function, how to leverage the powerful multi-attach feature, and understand the importance of EBS snapshots for data backup and recovery. Perfect for aspiring cloud professionals looking to build a strong foundation in AWS storage solutions.

What you will learn:

• How to create a Linux EC2 instance from scratch in AWS.

• Steps to securely SSH into a Linux machine hosted on AWS.

• How to resize and increase the EBS volume size of an EC2 instance.

• Using Linux commands effectively to manage storage volumes.

• Best practices for resizing EBS volumes with zero downtime.

What you will learn:

• The core concepts of Amazon DynamoDB and how it functions as a NoSQL database.

• How DynamoDB efficiently manages data with seamless scalability and high availability.

• Real-world use cases of DynamoDB, such as supporting gaming companies with massive data loads.

• An introduction to DynamoDB Accelerator (DAX) and how it provides microsecond latency for read-heavy applications.

• The advantages of using DynamoDB for building fast, reliable, and highly scalable applications.

What you will learn:

• Learn how to create a DynamoDB table using the AWS Management Console.

• Define a partition key and sort key for efficient data organization.

• Insert data into the DynamoDB table and explore its functionality.

• Verify the inserted data directly in the DynamoDB table.

• A beginner-friendly, practical guide to mastering the basics of DynamoDB.

This hands-on video is perfect for cloud beginners or anyone looking to develop a strong foundation in Amazon DynamoDB!

Let's learn the basics of Amazon DynamoDB Accelerator ( DAX ) and it's advantages.

In this video we will learn about basics theory of AWS Lambda function to get started with.

• Learn how to automate the management of EC2 instances using AWS Lambda functions.

• Discover how to write Python code to turn off EC2 instances when they are not needed.

• Explore how to terminate instances that are no longer required, ensuring cost efficiency.

• Gain insights into configuring AWS Lambda triggers for seamless automation.

• Perfect for cloud enthusiasts looking to optimize resource usage and reduce AWS costs.

This hands-on video provides practical guidance to make your cloud management smarter and more efficient!

In this lecture we will learn the basic theory concepts about AWS CodeDeploy to get started with.

In this lecture we will learn basic theory concept about Amazon Simple Queue Service (Amazon SQS)

In this lecture we will implement the concept of SQS Dead-Letter Queue in AWS console by doing hands on.

In this lecture we will learn about how to create a Virtual Private Cloud in AWS using the VPC wizard. We will also learn the basics of networking concepts like CIDR, Internet Gateway, Subnet etc

In this tutorial we will learn about IAM roles in AWS. How to create IAM role for EC2 instance and DynamoDB which can be later attached to an EC2 instance.

Learn how to query data stored in an S3 bucket using Amazon Athena in this hands-on tutorial ! From setting up an S3 bucket and uploading a CSV file to configuring Amazon Athena from scratch, we cover it all:

1. Create an S3 bucket and upload your CSV file from your local computer.

2. Set up Amazon Athena, including creating a workgroup and specifying the query results location.

3. Use AWS Glue Data Catalog to create a database, add and configure table properties for CSV data with a comma (,) delimiter, and define the schema.

4. Finally, run SQL queries on your data using Amazon Athena.

Perfect for beginners or anyone looking to efficiently query large datasets on AWS. Watch now and follow along!

Learn how to effectively use the Data API with Amazon Aurora Serverless in this step-by-step, hands-on tutorial. Perfect for developers looking to set up and configure a reliable dev/test database environment, this course covers:

• Creating and configuring a security group for the Aurora database with inbound and outbound rules.

• Setting up and configuring an RDS Aurora MySQL Serverless database.

• Generating credentials for the database, including creating a username and password, and applying a preconfigured security group.

• Establishing a connection to the Aurora database using the Data API and the generated credentials.

• Using the RDS Query Editor to create a new database, design a table, and insert dummy data values.

• Verifying the inserted values using SELECT query statements in Aurora Serverless.

Whether you're a beginner or seasoned professional, this tutorial equips you with the essential skills to manage serverless databases efficiently. Join us and elevate your database management expertise!

Welcome to our hands-on tutorial on Automatically Detecting PII Data In Amazon S3 Using Amazon Macie! In this video, we'll guide you through the process of setting up Amazon Macie to identify and protect sensitive information in your S3 buckets using End-to-End Architecture Diagram Automation.

What You'll Learn:

1. Introduction to Amazon Macie: Understand the basics of Amazon Macie and its capabilities.

2. Uploading PII Files to S3: Steps to upload files containing PII data to an Amazon S3 bucket.

3. Configuring Amazon Macie: How to configure Amazon Macie to detect PII data and use Custom Data Identifiers with RegEx as per business requirements.

4. Integrating with Amazon EventBridge and SNS: Set up integrations to send email notifications for any PII data findings in S3 buckets.

Steps Covered:

1. Introduction to Amazon Macie: Overview of the service and its features.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Macie.

3. Uploading PII Files to S3: Steps to upload files containing PII data to an Amazon S3 bucket.

4. Configuring Amazon Macie: Detailed steps to configure Amazon Macie to detect PII data and create Custom Data Identifiers using RegEx.

5. Integrating with Amazon EventBridge: How to integrate Amazon Macie findings with Amazon EventBridge.

6. Setting Up SNS Notifications: Configure Amazon SNS to send email notifications for PII data findings.

7. Reviewing Results: How to interpret and utilize the findings provided by Amazon Macie.

In this comprehensive hands-on tutorial, we dive deep into the world of AWS Data Engineering. Join us as we demonstrate essential data engineering tasks and best practices using AWS services.

Here’s what we’ll cover:

1. Data Quality Checks: Ensure row count is greater than 99 and verify the presence of primary keys in all records.

2. Filter Expression: Apply filter expressions to refine your data.

3. Custom SQL Expression: Fetch only two specific columns from a table using a custom SQL query.

4. Inner Join Using AWS Glue: Learn to perform efficient inner joins with AWS Glue.

5. File Format Conversion: Convert source files from .csv to Parquet using AWS Glue jobs.

6. Schema Inference with AWS Glue Crawler: Automatically infer the schema from S3 source files.

Watch as we demonstrate how to upload input files to an S3 bucket's "source" folder from your local computer and store the transformed files in the "target" folder using Glue jobs. We’ll guide you through every step to ensure your data pipelines are robust, efficient, and cost-effective.

Welcome to our hands-on project tutorial on Redacting PII Data Using Amazon Transcribe In this video, we'll guide you through an end-to-end project designed for restaurant businesses that accept orders via phone calls. Learn how to use Amazon Transcribe to redact sensitive customer information such as names, phone numbers, and addresses from recorded audio files.

What You'll Learn:

1. Recording Orders: How to record customer orders via phone calls and save them as .wav files.

2. Uploading to S3: Steps to upload the recorded .wav files to an Amazon S3 bucket.

3. Creating Transcription Jobs: How to create transcription jobs using Amazon Transcribe to extract text from the audio files.

4. Redacting PII Data: Techniques to automatically redact personally identifiable information (PII) from the transcriptions.

5. Forwarding to Chef: How to forward the redacted transcription to the chef for preparing the dishes while ensuring customer privacy.

Steps Covered:

1. Introduction to Amazon Transcribe: Overview of the service and its capabilities.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Transcribe.

3. Recording and Uploading Audio Files: Record customer orders and upload the .wav files to an S3 bucket.

4. Creating Transcription Jobs: Create transcription jobs in Amazon Transcribe and select the uploaded audio files for transcription.

5. Redacting PII Data: Use Amazon Transcribe's PII redaction feature to automatically hide sensitive customer information.

6. Reviewing and Forwarding Transcriptions: Review the redacted transcriptions and forward them to the chef for order preparation.

Embark on an exciting hands-on journey to revolutionize logistics with cutting-edge AI! In this step-by-step tutorial, you'll learn how to create an end-to-end IT project for predicting the actual shipping days of products—without writing a single line of code, thanks to Amazon SageMaker AI Canvas.

What you'll achieve:

• Upload shipment and product data as .csv files from your computer to AWS S3.

• Configure a SageMaker AI domain, create a user profile, and set up your working environment.

• Seamlessly import shipment and product data into SageMaker Canvas and perform an inner join operation.

• Utilize SageMaker Canvas' Chat for Data Prep to generate an insightful graph comparing actual vs. expected shipping dates—automatically backed by AI-generated code.

• Drop unnecessary columns and set up regression analysis in SageMaker Data Wrangler for accurate predictions.

• Build, train, and export a machine learning model to predict the target variable: actual shipping days.

• Download the model output as a .csv file for actionable insights, and even run a single prediction directly in SageMaker Canvas.

This video is perfect for professionals in logistics and supply chain management, tech enthusiasts, and AI beginners eager to dive into no-code AI model building. Join today and empower yourself to optimize logistic operations with predictive analytics!

Welcome to our comprehensive tutorial on building a Chat Bot For a Burger Business Using Amazon Lex In this video, we'll guide you through the entire process, from creating intents and slot types to building and testing the chat bot in the AWS console.

What You'll Learn:

1. Setting up Amazon Lex for your burger restaurant

2. Creating intents to handle customer queries

3. Defining slot types for capturing specific information

4. Building the chat bot with step-by-step instructions

5. Testing the chat bot to ensure it works seamlessly

Welcome to our comprehensive guide on building a cybersecurity-focused face recognition web application! In this video, we’ll take you through the entire process of creating a robust and secure face recognition system using Claude 3 and Amazon Rekognition.

What You’ll Learn:

1. Setting Up AWS Services: Learn how to configure essential AWS services like Security Groups, Application Load Balancer, and Route 53 for a secure and scalable architecture.

2. Development Environment: Get hands-on with AWS Cloud9 to set up your development environment.

3. Containerization: Understand how to create and manage Docker containers using Amazon ECS Cluster and Task Definition.

4. Image Storage and Management: Discover how to use Amazon ECR for storing and managing Docker images.

5. Face Recognition Integration: Integrate Claude 3 with Amazon Rekognition to build a powerful face recognition system.

6. Security First: We emphasize best practices in cybersecurity to ensure your application is secure from the ground up.

7. End-to-End Architecture: Follow along as we build the entire architecture from scratch, ensuring you have a clear understanding of each component and how they work together.

Who Is This For ?

Whether you’re a developer, a cybersecurity enthusiast, or someone looking to enhance their AWS skills, this video has something for you!

In this step-by-step hands-on tutorial, learn how to assess and address security vulnerabilities in AWS EC2 instances using Amazon Inspector. This detailed guide walks you through the entire process, including:

• Creating an AWS EC2 Instance from scratch, including configuring the instance type and generating a key pair for SSH access.

• Deliberately opening additional ports (21, 23, 24) to simulate potential vulnerabilities for detection.

• Using EC2 Instance Connect to SSH into the Linux instance and installing the Amazon Inspector Agent.

• Setting up an Assessment Target in Amazon Inspector to monitor your EC2 instance.

• Creating an Assessment Template for your desired security checks.

• Running an Amazon Inspector assessment and downloading the detailed PDF report of findings.

• Verifying open ports (21, 23, 24) flagged as vulnerabilities in the assessment report.

This hands-on tutorial provides a real-world approach to identifying and mitigating vulnerabilities, emphasizing the importance of thorough security assessments. Whether you’re preparing for AWS certification, advancing your cloud security skills, or both, this video equips you with the knowledge to confidently use Amazon Inspector for EC2 instance security.

Ready to boost your AWS security expertise? Watch and follow along now!

In this tutorial, we dive deep into the world of social media sentiment analysis using Amazon Comprehend. Learn how to harness the power of AWS to analyze sentiments from various social media platforms and gain valuable insights into public opinion in an end-to-end project.

What You’ll Learn:

1. Setting Up Your Environment: How to store your input files in an Amazon S3 bucket. Using Amazon Comprehend: Step-by-step guide to analyzing social media posts for sentiment.

2. Data Processing: How to organize and store output files, including the corresponding post, social media platform name, and sentiment, in a structured format.

3. Real-World Application: Practical examples and use cases to help you understand the impact of sentiment analysis on business decisions.

This Hands-On Tutorial contains follow along with detailed instructions and code.

Unlock the power of DynamoDB with DAX! In this comprehensive tutorial, we’ll walk you through every step of setting up and customizing a DynamoDB DAX Cluster in Amazon cloud. Here’s what you’ll learn:

1. Set Up Amazon EC2 Instances: Utilize Amazon Machine Images and key pairs for seamless SSH authentication.

2. Create a Go Application: Develop an application and establish a sample DynamoDB table.

3. Execute and Measure Commands: Perform GetItem, Query, and Scan operations with DynamoDB and record execution times.

4. Boost Performance with DAX: Experience the speed difference as you repeat the same operations using a DynamoDB Accelerator (DAX) Cluster.

Whether you're a developer or cloud enthusiast, this step-by-step guide will help you optimize your database interactions. Tune in to elevate your DynamoDB expertise!