AI-100: Designing and Implementing an Azure AI Solutions
What you'll learn
- Ingest, transform, and prepare data for AI solutions
- Design and implement end-to-end AI solutions on Microsoft Azure
- Monitor and optimize AI solutions deployed on Microsoft Azure
- Secure AI solutions on Microsoft Azure
- You will be able to integrate and get best results for any computer vision or Natural Language processing tasks.
- Ability to show and include Machine Learning applications in your app
- Learn Microsoft Azure - Cloud platform cognitive services like Face, Vision, Text API
- This path is intended for learners who are familiar with common AI workflows and concepts, but who do not have experience applying these concepts using Microsoft Azure services.
- Basic idea about HTTP, REST
- Usage of Visual Studio
UPDATE : Please note that this course will be upgraded to AI 102 with the new curriculum.
This means that even if you are preparing for AI 100, you can continue to use this course for AI 102 preparation.
Microsoft Azure offers a spread of services designed to work together to enable rapid development of high-performance AI solutions. This skill teaches how these Azure services work together to enable you to design, implement, operationalize, monitor, optimize, and secure your AI solutions on Microsoft Azure. This path is designed to address the Microsoft AI-100 certification exam.
With cognitive services you will be able to build all such or even more types of applications.
Here is the course content covered in this course :
Analyze solution requirements (25-30%)
Recommend Azure Cognitive Services APIs to meet business requirements
· select the processing architecture for a solution
· select the appropriate data processing technologies
· select the appropriate AI models and services
· identify components and technologies required to connect service endpoints
· identify automation requirements Map security requirements to tools, technologies, and processes · identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
· identify which users and groups have access to information and interfaces
· identify appropriate tools for a solution
· identify auditing requirements Select the software, services, and storage required to support a solution
· identify appropriate services and tools for a solution
· identify integration points with other Microsoft services
· identify storage required to store logging, bot state data, and Azure Cognitive Services output
Design AI solutions (40-45%)
Design solutions that include one or more pipelines
· define an AI application workflow process
· design a strategy for ingest and egress data
· design the integration point between multiple workflows and pipelines
· design pipelines that use AI apps
· design pipelines that call Azure Machine Learning models
· select an AI solution that meet cost constraints Design solutions that uses Cognitive Services
· design solutions that use vision, speech, language, knowledge, search, and anomaly detection APIs Design solutions that implement the Microsoft Bot Framework
· integrate bots and AI solutions
· design bot services that use Language Understanding (LUIS)
· design bots that integrate with channels
· integrate bots with Azure app services and Azure Application Insights Design the compute infrastructure to support a solution
· identify whether to create a GPU, FPGA, or CPU-based solution
· identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure
· select a compute solution that meets cost constraints Design for data governance, compliance, integrity, and security
· define how users and applications will authenticate to AI services
· design a content moderation strategy for data usage within an AI solution
· ensure that data adheres to compliance requirements defined by your organization
· ensure appropriate governance of data
· design strategies to ensure that the solution meets data privacy regulations and industry standards
Implement and monitor AI solutions (25-30%)
Implement an AI workflow
· develop AI pipelines
· manage the flow of data through the solution components
· implement data logging processes
· define and construct interfaces for custom AI services
· create solution endpoints
· develop streaming solutions Integrate AI services and solution components
· configure prerequisite components and input datasets to allow the consumption of Azure Cognitive Services APIs
· configure integration with Azure Cognitive Services
· configure prerequisite components to allow connectivity to the Microsoft Bot Framework
· implement Azure Cognitive Search in a solution Monitor and evaluate the AI environment
· identify the differences between KPIs, reported metrics, and root causes of the differences
· identify the differences between expected and actual workflow throughput
· maintain an AI solution for continuous improvement
· monitor AI components for availability
· recommend changes to an AI solution based on performance data
Hope this course would be informative to you. Please reach out to me if you have any questions.
Who this course is for:
- Participants who intend to learn common AI workflows and concepts
- Participants who want to Secure AI solutions
- Participants preparing for AI 100 Microsoft Certification
Meet Anand, a seasoned IT professional with over 20 years of experience and a specialization in Active Directory. Anand is a cloud computing expert who has been working in this field since 2012. He holds multiple vendor and vendor-neutral certifications in cloud computing and cyber security, making him a trusted advisor for organizations looking to transition to the cloud.
With his extensive experience and expertise, Anand has provided consultation to numerous organizations and helped them set up cloud infrastructure and optimize their cloud operations. He also has a strong inclination towards information security and data engineering platforms, making him a go-to resource for clients seeking guidance in these areas.
Anand's passion for sharing knowledge and educating others is evident through his blog articles, YouTube videos, and Udemy courses. He is committed to helping others understand complex cloud and security concepts in a simple and understandable way.
If you are looking for a cloud computing expert with extensive experience, a passion for knowledge-sharing, and a commitment to providing the best solutions for your organization, look no further than Anand. Contact him today to discuss how he can help take your cloud infrastructure and security to the next level.
Microsoft Certified Trainer ( MCT )
SY0-401 : CompTIA Security +
Scrum Certified master ( SCRUM )
Certified Network Defender ( CND – EC-Council )
Certified Ethical hacker ( CEH – EC-Council )
70-640 MS Active Directory
70-533 MS Azure Administration
70-534 MS Azure Architecture
AWS certified solutions Architect – Associate
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Google Cloud Platform-Cloud Architect (GCP)
Certified Cloud Security Knowledge ( CCSK )
Microsoft Security series Certified
MS-500 , Az -500 , SC-900 , SC 200 , SC-300 & SC -100