Coursera Instructor Network
Building GenAI Applications and Agents 专项课程
Coursera Instructor Network

Building GenAI Applications and Agents 专项课程

Build AI agents and GenAI applications with Python. Learn to create AI agents and applications using ChatGPT API and LangChain. Python required.

Starweaver
Ritesh Vajariya
Manas Dasgupta

位教师:Starweaver

包含在 Coursera Plus

深入学习学科知识
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推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识
中级 等级

推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Build AI agents and GenAI applications using ChatGPT API, LangChain, and advanced frameworks like CrewAI and AutoGen.

  • Design and implement RAG applications that combine LLMs with vector databases for intelligent data analysis and automation.

  • Select and optimize the right LLM models from Hugging Face based on performance, cost, and specific application requirements.

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授课语言:英语(English)
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August 2025

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  • 通过 Coursera Instructor Network 获得职业证书

专业化 - 6门课程系列

您将学到什么

您将获得的技能

类别:Prompt Engineering
类别:Authentications
类别:Application Programming Interface (API)
类别:OpenAI
类别:Performance Tuning
类别:ChatGPT
类别:Debugging
类别:Key Management
类别:Large Language Modeling

您将学到什么

  • Describe the types, functions, and practical applications of AI agents across various industries.

  • Implement AI agents using advanced tools, applying them to solve real-world problems effectively.

  • Evaluate AI systems by their performance, addressing limitations, and leveraging collaborative frameworks.

  • Analyze the ethical and societal implications of AI, creating guidelines for responsible innovation and deployment.

您将获得的技能

类别:Artificial Intelligence
类别:Agentic systems
类别:Prompt Engineering Tools
类别:Large Language Modeling
类别:OpenAI
类别:Generative AI
类别:Artificial Intelligence and Machine Learning (AI/ML)
类别:LLM Application
类别:Tool Calling
类别:Generative AI Agents
类别:Automation
类别:Responsible AI
类别:Business Process Automation
类别:ChatGPT
类别:LangChain
类别:Innovation
类别:Data Ethics
类别:Performance Testing
Implementation of GenAI Agents

Implementation of GenAI Agents

第 3 门课程4小时

您将学到什么

  • Apply core principles of AI agent architecture to design a basic agent system

  • Construct a development environment for building and testing AI agents

  • Develop a functional AI agent using a chosen framework (e.g., LangChain or AutoGen)

  • Evaluate and optimize an AI agent's performance through advanced feature integration

您将获得的技能

类别:Performance Tuning
类别:Generative AI Agents
类别:Artificial Intelligence
类别:Generative AI
类别:Programming Principles
类别:LangChain
类别:Agentic systems
类别:Virtual Environment
类别:Development Environment
类别:Performance Testing
类别:Design
类别:Scalability
类别:OpenAI
类别:LLM Application

您将学到什么

  • Analyze foundational LangChain principles, emphasizing core architecture and components for a strong base in application development.

  • Design and implement a basic application utilizing LangChain, demonstrating practical application of the framework in solving real-world problems.

  • Assess LangChain problem-solving strategies for programming challenges, applying critical thinking to choose the most effective solutions.

  • Critique LangChain's evolution in the AI landscape, forecasting impacts and innovations for future application development.

您将获得的技能

类别:Application Development
类别:LangChain
类别:Large Language Modeling
类别:Natural Language Processing
类别:Generative AI
类别:Prompt Engineering
类别:LLM Application
类别:Artificial Intelligence

您将学到什么

  • Navigate through the Hugging Face Ecosystem

  • Comparing Models using various Factors and Practical Considerations

  • Using a Model from Hugging Face

  • Determine the most suitable model for a given task by scoring the results from each candidate model on a variety of parameters.

您将获得的技能

类别:Large Language Modeling
类别:LLM Application
类别:Applied Machine Learning
类别:Prompt Engineering
类别:Generative Model Architectures
类别:Machine Learning Methods

您将学到什么

  • Demonstrate Large Language Model capabilities in Natural Language based Automations.

  • Demonstrate the use of RAG Applications in a range of problems they can solve.

  • Use Vector Databases as a Storage Medium of Language Embeddings in RAG Applications.

  • Develop RAG Applications using LLM Frameworks, Models and Vector Databases.

您将获得的技能

类别:LangChain
类别:Large Language Modeling
类别:Google Gemini
类别:OpenAI
类别:Tool Calling
类别:ChatGPT
类别:Prompt Engineering
类别:Generative AI Agents
类别:LLM Application

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位教师

Starweaver
Coursera Instructor Network
446 门课程818,636 名学生
Ritesh Vajariya
Coursera Instructor Network
17 门课程7,396 名学生
Manas Dasgupta
Coursera Instructor Network
10 门课程8,088 名学生

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