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Building GenAI Applications and Agents Specialization

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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

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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
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

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

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Specialization - 6 course series

What you'll learn

Skills you'll gain

Category: Authentications
Category: Application Programming Interface (API)
Category: Prompt Engineering
Category: Performance Tuning
Category: OpenAI
Category: Artificial Intelligence
Category: Restful API
Category: Key Management
Category: Generative AI
Category: Large Language Modeling
Category: ChatGPT

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

Category: Agentic systems
Category: Artificial Intelligence
Category: Ethical Standards And Conduct
Category: Innovation
Category: Prompt Engineering
Category: Business Process Automation
Category: Automation
Category: Software Development Tools
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Generative AI Agents
Category: Performance Analysis

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

Category: Software Architecture
Category: Generative AI Agents
Category: Design
Category: OpenAI
Category: Scalability
Category: Artificial Intelligence
Category: Development Environment
Category: Programming Principles
Category: Performance Testing
Category: Performance Tuning
Category: Large Language Modeling

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

Category: Application Development
Category: Natural Language Processing
Category: Large Language Modeling
Category: Artificial Intelligence
Category: Application Frameworks
Category: Generative AI
Category: Prompt Engineering
Category: OpenAI

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

Category: Natural Language Processing
Category: Large Language Modeling
Category: Generative AI Agents
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: PyTorch (Machine Learning Library)
Category: Programming Principles
Category: Applied Machine Learning

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

Category: Generative AI
Category: Data Storage Technologies
Category: Large Language Modeling
Category: Data Store
Category: Application Development
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Natural Language Processing
Category: OpenAI
Category: ChatGPT
Category: Prompt Engineering

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Instructors

Starweaver
Coursera Instructor Network
411 Courses766,926 learners
Ritesh Vajariya
Coursera Instructor Network
13 Courses5,410 learners
Manas Dasgupta
Coursera Instructor Network
10 Courses6,480 learners

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