Coursera Instructor Network
Building GenAI Applications and Agents Specialization
Coursera Instructor Network

Building GenAI Applications and Agents Specialization

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

Instructors: Starweaver

Included with Coursera Plus

Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Earn a Certificate
With paid plans
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Earn a Certificate
With paid plans

What you'll learn

  • 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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Taught in English
Recently updated!

August 2025

15 practice exercises

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Specialization - 6 course series

What you'll learn

Skills you'll gain

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

What you'll learn

  • 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.

Skills you'll gain

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

What you'll learn

  • 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

Skills you'll gain

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

What you'll learn

  • 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.

Skills you'll gain

LangChain, Application Development, LLM Application, Large Language Modeling, Artificial Intelligence, Generative AI, Prompt Engineering, and Natural Language Processing

What you'll learn

  • 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.

Skills you'll gain

LLM Application, Large Language Modeling, Prompt Engineering, Machine Learning Methods, Applied Machine Learning, and Generative Model Architectures

What you'll learn

  • 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.

Skills you'll gain

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

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Instructors

Starweaver
Coursera Instructor Network
448 Courses831,185 learners
Ritesh Vajariya
Coursera Instructor Network
17 Courses7,858 learners
Manas Dasgupta
Coursera Instructor Network
10 Courses8,453 learners

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