Code and framework based agent development

本课程是 Microsoft AI Agents: From Foundations to Applications 专业证书的一部分

位教师： Microsoft

访问权限由 New York State Department of Labor 提供

4个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

24 项作业

授课语言：英语（English）

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积累 Design and Product 领域的专业知识

本课程是 Microsoft AI Agents: From Foundations to Applications 专业证书专项课程的一部分

在注册此课程时，您还会同时注册此专业证书。

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该课程共有4个模块

This course is designed to transition experienced developers into AI agent specialists through intensive, hands-on coding. You'll build production-ready systems by using AI frameworks and integrating advanced language models. You'll benefit by learning to build secure, cost-optimized agents and connect them to the Microsoft 365 ecosystem.

By the end of this course, you will be able to: - Integrate Azure OpenAI Service for complex reasoning and implement prompt chaining strategies. - Develop professional conversational bots using Python and the Bot Framework. - Simplify AI orchestration by creating reusable plugins and memory systems with Semantic Kernel. - Connect agents to the Microsoft 365 ecosystem using the Microsoft Graph API for data access and report generation. - Implement production-ready features, including error handling, security, and cost-optimization.

Learn to integrate language models by utilizing GPT-4 for complex reasoning and implementing sophisticated prompt engineering strategies. You'll build cost management systems using Azure Monitor, optimize token usage, and create sustainable AI development practices that balance capability with budget.

涵盖的内容

7个视频3篇阅读材料6个作业

7个视频总计28分钟

Course introduction 4分钟
The power of advanced language models 3分钟
Setting up Azure OpenAI 5分钟
Prompt engineering as a discipline 4分钟
Advanced prompting patterns 6分钟
The economics of AI APIs 3分钟
Cost management implementation 4分钟

3篇阅读材料总计30分钟

Course syllabus 10分钟
Azure OpenAI service architecture 10分钟
Optimization strategies 10分钟

6个作业总计180分钟

OpenAI production graded quiz 30分钟
Activity: Research agent foundation with OpenAI 45分钟
Introduction to AI agents knowledge check 15分钟
Activity: Research prompt workshop 45分钟
Prompt engineering for specialized analysis knowledge check 15分钟
Activity: Cost monitoring and optimization 30分钟

Learn professional agent development by building sophisticated conversational bots using Python and Bot Framework with production-ready practices. You'll implement proper error handling, testing with pytest, security measures, and create a portfolio-worthy GitHub repository demonstrating your full-stack AI capabilities.

涵盖的内容

6个视频2篇阅读材料6个作业

6个视频总计29分钟

Why Python for AI agents 5分钟
Building your first Python bot 5分钟
Bot framework architecture 3分钟
Advanced bot development 5分钟
Production excellence 5分钟
Building production systems 6分钟

2篇阅读材料总计20分钟

Python agent architecture 10分钟
Professional development practices 10分钟

6个作业总计210分钟

Bot framework development and deployment graded quiz 30分钟
Activity: Python agent development bootcamp 45分钟
Building with Azure AI Foundry's agents interface knowledge check 15分钟
Activity: Research bot implementation 45分钟
Bot framework development with Python SDK knowledge check 15分钟
Activity: Enterprise research bot with GitHub portfolio 60分钟

Simplify AI orchestration using Semantic Kernel to create reusable plugins and implement memory systems for your agents. You'll build market research capabilities through composable functions, understand memory architecture for context retention, and compare SK's advantages over traditional development approaches.

涵盖的内容

5个视频3篇阅读材料6个作业

5个视频总计21分钟

Why Semantic Kernel 4分钟
Building with Semantic Kernel 5分钟
The plugin ecosystem 3分钟
Plugin development deep dive 5分钟
Building memory systems 4分钟

3篇阅读材料总计30分钟

Semantic Kernel architecture 10分钟
Memory in AI agents 10分钟
Memory implementation strategies 10分钟

6个作业总计180分钟

Semantic Kernel development graded quiz 30分钟
Activity: Semantic Kernel foundation 30分钟
Semantic Kernel fundamentals 15分钟
Activity: Research plugin development 45分钟
Building plugins and skills knowledge check 15分钟
Activity: Memory implementation 45分钟

Connect your agents to the enterprise by implementing Microsoft Graph API for file access and building data integration pipelines. You'll create automated report generation systems, process data from multiple sources, and compile a comprehensive portfolio showcasing your evolution from basic agents to integrated enterprise solutions.