Course
digicode: AI103
Develop AI Apps and Agents on Azure – Intensive Training (AI-103)
AI-103
Course facts
Download as PDF- Identifying foundational AI capabilities, appropriate developer tools, and the necessary process for responsible AI solution development within Microsoft Foundry
- Exploring and evaluating AI models using the model catalog, benchmark metrics (quality, safety, cost, performance), and both manual and automated performance evaluation approaches
- Building generative AI applications, such as chat apps, by selecting endpoints, authentication methods, client SDKs, and using APIs like Responses and ChatCompletions
- Optimizing model output using prompt engineering techniques (system messages, few-shot learning), fine-tuning, and grounding language models with Retrieval Augmented Generation (RAG)
- Developing and deploying AI agents using the Microsoft Foundry Agent Service, extending their capabilities with custom tools and integrating them into applications like Microsoft 365
- Solving knowledge problems by configuring data sources (e.g., Azure AI Search, SharePoint) for knowledge bases and connecting agents to real-time information via Foundry IQ
- Implementing multi-agent solutions by understanding different orchestration patterns, leveraging the A2A protocol, and controlling workflow execution using nodes and conditional logic
- Deploying specialized generative AI models for advanced tasks including speech recognition/synthesis, content understanding, image/video generation, and document intelligence
1 Develop generative AI apps in Azure
Generative artificial intelligence (AI) is becoming more accessible through comprehensive development platforms like Microsoft Foundry. Learn how to build generative AI applications that use language models to interact with your users.
2 Develop AI agents on Azure
Generative Artificial Intelligence (AI) is becoming more functional and accessible, and AI agents are a key component of this evolution. This module will help you understand the AI agents, including when to use them and how to build them, using Microsoft Foundry Agent Service and Microsoft Agent Framework. By the end of this learning module, you will have the skills needed to develop AI agents on Azure.
3 Develop natural language solutions in Azure
Natural language solutions use language models to interpret the semantic meaning of written or spoken language, and in some cases respond based on that meaning. You can use Microsoft Foundry to develop AI apps and agents that can analyze text, transcribe and synthesize speech, and translate languages.
4 Extract insights from visual data on Azure
Use generative AI, computer vision, and Content Understanding capabilities in Azure to extract insights from visual data, supporting scenarios like:
- Image analysis
- Image and video generation
- Content Understanding and enrichment
- Visual search and classification
- Digital asset management (DAM)
- Multimodal AI solutions
This course is aimed at software engineers concerned with building, managing and deploying AI solutions that leverage Microsoft Foundry.
- Familiarity with Python
- Knowledge on using APIs and SDKs to build agents and generative AI solutions on Azure