Courses / Python

Agentic AI, RAG, LangGraph, and Model Context Protocol (MCP) with Python

0.0 (0 ratings) Python
1 enrolled 30 lessons

What you'll learn

  • Welcome to Agentic AI and Python: Course Overview
  • Setting Up Your Python Environment for AI Projects
  • Understanding Agentic AI: Concepts and Use Cases
  • Intro to Retrieval-Augmented Generation (RAG) Architecture
  • Exploring LangGraph: Building Language Knowledge Graphs
  • Model Context Protocol (MCP): Principles and Benefits
  • Python Refresher: OOP, Data Structures, and Async Basics
  • Creating Your First Agentic AI Program in Python
  • Implementing RAG: Querying External Knowledge Sources
  • Building LangGraph Nodes and Edges with Python

+ 20 more topics

About this course

Master the cutting-edge concepts of Agentic AI, Retrieval-Augmented Generation (RAG), LangGraph, and the Model Context Protocol (MCP) using Python. This intermediate course guides you through practical programming, automation, and API integrations with hands-on projects, gamified challenges, and supportive AI mentoring to build real-world AI-powered applications.

Curriculum

  • 1 Welcome to Agentic AI and Python: Course Overview Quiz
  • 2 Setting Up Your Python Environment for AI Projects Quiz
  • 3 Understanding Agentic AI: Concepts and Use Cases Quiz
  • 4 Intro to Retrieval-Augmented Generation (RAG) Architecture Quiz
  • 5 Exploring LangGraph: Building Language Knowledge Graphs Quiz
  • 6 Model Context Protocol (MCP): Principles and Benefits Quiz
  • 7 Python Refresher: OOP, Data Structures, and Async Basics Quiz
  • 8 Creating Your First Agentic AI Program in Python Quiz
  • 9 Implementing RAG: Querying External Knowledge Sources Quiz
  • 10 Building LangGraph Nodes and Edges with Python Quiz
  • 11 Integrating MCP for Context-Aware Model Interactions Quiz
  • 12 Designing Conversational Flows using Agentic AI Quiz
  • 13 Visualizing LangGraph with Supportive AI-Generated Graphics Quiz
  • 14 Automating API Calls with Python and RAG
  • 15 Gamify Your AI Agent: Interactive Challenge Setup
  • 16 Debugging and Testing Agentic AI Programs Quiz
  • 17 Advanced LangGraph Queries for Enhanced Context
  • 18 Dynamic Context Management with MCP in Python
  • 19 Building Multi-Agent Coordination using Agentic AI
  • 20 Deploying AI Agents via FastAPI Endpoints
  • 21 Handling Rate Limits and API Errors Gracefully
  • 22 Visual Feedback: Creating Supportive UI with Python Libraries
  • 23 Using AI Mentors to Guide Python Code Improvement
  • 24 Integrating External Data Sources into RAG Pipelines
  • 25 Optimizing LangGraph for Performance and Scalability
  • 26 Implementing Security Best Practices for AI Agents
  • 27 Real-World Project: Contextual Chatbot with Agentic AI and MCP
  • 28 Gamified Assessment: Building a Trivia Bot with LangGraph
  • 29 Future Trends: Expanding Agentic AI with Python Automation
  • 30 Course Wrap-Up and Next Steps in AI Programming

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