Description
Stay ahead of the curve with our intensive 5-day certification program. This course is the official successor to AI-900 and AI-102, redesigned to focus on the future of development: Generative AI and Agentic Applications.
Participants will gain hands-on expertise in building intelligent agents, implementing complex knowledge connections, and leveraging multimodal capabilities to process sophisticated content. Elevate your teamโs ability to deploy functional, tool-augmented AI solutions in just one week.
In this intensive 5-day bootcamp, students will earn their MCA Azure AI App & Agent Developer Associate credential by completing both the AI-901 and AI-103 exams. This instructor-led, hands-on experience provides the practical skills necessary to secure Azure AI environments, with all certification exams conveniently administered during the course.
The Microsoft Certified Cloud and AI Security Engineer Associate boot camp is taught using Microsoft Official Courseware
AI-901T00: Microsoft Azure AI Fundamentals
AI-103T00: Azure AI Apps and Agents Developer Associate
Everything You Need to Succeed – What’s Included
Microsoft Certified Trainer (MCT) Instructor Led Live Training
2 Microsoft Official Courses (AI-901 / AI-103)
2 Microsoft Official Exam Vouchers (AI-900 / AI-103)
2 Retake Vouchers (1 per exam, if needed)
Microsoft Official Hands on Labs
Microsoft Vetted Practice Exams
Onsite & Online Pearson Vue Testing
Topics Covered in this Official Boot Camp:
Introduction to AI concepts
Introduction to AI
Generative AI and agents
Text and natural language
Speech
Computer vision
Information extraction
Responsible AI
Introduction to generative AI and agents
Large language models (LLMs)
Prompts
AI agents
Introduction to natural language processing concepts
Tokenization
Statistical text analysis.
Semantic language models
Introduction to AI speech concepts
Speech-enabled solutions
Speech recognition
Speech synthesis
Introduction to computer vision concepts
Computer vision tasks and techniques
Images and image processing
Convolutional neural networks
Vision transformers and multimodal models
Image generation
Introduction to AI-powered information extraction concepts
Overview of information extraction
Optical character recognition (OCR)
Field extraction and mapping
Get started with AI in Azure
Understand Azure
Developing AI apps on Azure
Microsoft Foundry for AI
Using Microsoft Foundry endpoints
Get started with Generative AI and agents in Azure
Generative AI models
Using a generative AI model
Creating an agent
Get started with text analysis in Azure
Understand text analysis in Foundry
Create a client application that analyzes text
Use Azure Language with an agent
Get started with Speech in Azure
Speech recognition
Speech synthesis
Creating a speech-capable agent
Get started with Computer vision in Azure
Multimodal models for image analysis
Image generation models
Video generation models
Get started with AI-powered information extraction in Azure
Extract information from documents
Extract information from audio and video
Plan and prepare to develop AI solutions on Azure
What is AI?
Microsoft Foundry
Foundry Tools
Developer tools and SDKs
Responsible AI
Select, deploy, and evaluate Microsoft Foundry models
Explore the model catalog
Select models using benchmarks
Deploy models to endpoints
Evaluate model performance
Develop a generative AI chat app with Microsoft Foundry
Explore with the model playground
Choose an endpoint and SDK
Generate responses with the Responses API
Generate responses with the ChatCompletions API
Develop generative AI apps that use tools
What are tools?
Use the code_interpreter tool
Use the web_search tool
Use the file_search tool
Use the function tool
Optimize generative AI model performance with Microsoft Foundry
Optimize model output with prompt engineering
Ground your model with Retrieval Augmented Generation
Fine-tune a model for consistent behavior
Compare and combine optimization strategies
Implement a responsible generative AI solution in Microsoft Foundry
Plan a responsible generative AI solution
Map potential harms
Measure potential harms
Mitigate potential harms
Manage a responsible generative AI solution
Develop AI agents with Microsoft Foundry and Visual Studio Code
Understand AI agents and Microsoft Foundry Agent Service
Explore development approaches
Build your first agent in Microsoft Foundry
Set up Visual Studio Code for agent development
Configure and manage agents in Visual Studio Code
Extend agent capabilities with tools
Test, deploy, and integrate agents
Integrate custom tools into your agent
Why use custom tools
Options for implementing custom tools
How to integrate custom tools
Integrate MCP Tools with Azure AI Agents
Understand MCP tool discovery
Integrate agent tools using an MCP server and client
Use Azure AI agents with MCP servers
Build knowledge-enhanced AI agents with Foundry IQ
Understanding RAG for agents
Explore Foundry IQ
Configure data sources for knowledge bases
Configure retrieval with Foundry IQ
Integrate your agent with Microsoft 365
Understand Foundry agent publishing options
Publish an agent from Foundry portal to Teams
Advanced โ Use Microsoft 365 Agents Toolkit
Access Microsoft 365 data with Work IQ
Test and iterate your integrated agent
Build agent-driven workflows using Microsoft Foundry
Understand Workflows
Identify Workflow Patterns
Create workflows in Microsoft Foundry
Add Agents to a Workflow
Apply Power Fx in Workflows
Maintain Workflows in Microsoft Foundry
Use workflows in code
Develop an AI agent with Microsoft Agent Framework
Understand Microsoft Agent Framework AI agents
Create an Azure AI agent with Microsoft Agent Framework
Add tools to Azure AI agent
Orchestrate a multi-agent solution using the Microsoft Agent Framework
Understand the Microsoft Agent Framework
Understand agent orchestration
Use concurrent orchestration
Use sequential orchestration
Use group chat orchestration
Use handoff orchestration
Use Magnetic orchestration
Discover Azure AI Agents with A2A
Define an A2A agent
Implement an agent executor
Host an A2A server
Connect to your A2A agent
Analyze text with Azure Language in Foundry Tools
Azure Language in Microsoft Foundry Tools
Detect language
Extract entities
Extract personally identifiable information (PII)
Develop a text analysis agent with the Azure Language MCP server
Understand the Azure Language MCP server
Connect and use the Language MCP server with an agent
Develop a speech-capable generative AI application
Choose a speech-capable model
Transcribe speech
Synthesize speech
Create speech-enabled apps with Azure Speech in Microsoft Foundry Tools
Azure Speech in Foundry Tools
Use the Speech to Text API
Use the Text to Speech API
Configure audio format and voices
Use Speech Synthesis Markup Language
Develop a speech agent with the Azure Speech MCP server
Understand the Azure Speech MCP server
Connect and use the Speech MCP server with an agent
Develop an Azure Speech Voice Live Agent in Microsoft Foundry
Explore the Azure Voice Live API
Explore the AI Voice Live client library for Python
Create a Voice Live agent
Translate text and speech with Microsoft Foundry Tools
Translation in Microsoft Foundry
Translate text
Translate speech
Develop a vision-enabled generative AI application
Use a vision-capable model in the Microsoft Foundry portal
Develop a vision-based chat app
Generate images with AI
What are image-generation models?
Explore image-generation models in Microsoft Foundry portal
Create a client application that uses an image generation model
Generate videos with Microsoft Foundry
Deploy a video generating model
Generate video from a prompt
Generate video in Python
Analyze images with content Understanding
What is Content Understanding?
Analyze images with Content Understanding
Create a multimodal analysis solution with Azure Content Understanding
What is Azure Content Understanding?
Create a Content Understanding analyzer
Use the Content Understanding API
Create an Azure Content Understanding client application
Prepare to use the AI Content Understanding API
Create a Content Understanding analyzer
Analyze content
Extract data with Azure Document Intelligence
What is Azure Document Intelligence?
Use the Document Intelligence Studio
Use prebuilt models
Train and use custom models
Create a knowledge mining solution with Azure AI Search
What is Azure AI Search?
Extract data with an indexer
Enrich extracted data with AI skills
Search an index
Persist extracted information in a knowledge store
CAMPUS – Career Camps built out a stand alone training center (not a hotel conference room) with spacious classrooms, new desk, Herman Miller Aeron chairs & comfortable common areas. Each student has a dedicated desk with two monitors. Each classroom has a maximum of two rows – so everyone is able to be engaged without the “back row” feeling.




