LangChain- Develop AI Agents with LangChain & LangGraph

Master AI Agents with LangChain & LangGraph – Build cutting-edge LLM applications! This updated course (LangChain v1.0+) is designed for software developers, data scientists, and AI/ML engineers looking to harness the power of Agentic AI.

What You'll Learn:

• LangChain & LangGraph: Quickly leverage these powerful libraries for LLM applications and Agentic AI development.
• Agent Development: Learn to build sophisticated AI agents capable of complex tasks.
• Prompt Engineering: Master techniques like few-shot prompting, Chain of Thought, and ReAct prompting to optimize LLM outputs.
• Context Engineering: Understand how to effectively manage and utilize context for improved LLM performance.
• Retrieval Augmented Generation (RAG): Implement RAG for enhanced LLM knowledge and accuracy.
• Vectorstores: Explore vectorstores like Pinecone, FAISS, and Chroma for efficient data retrieval.
• Open Source Models: Work with and integrate open source models into your LLM projects.
• Tools & Function Calling: Utilize OpenAI Functions and tool calling to extend LLM capabilities.
• Memory Management: Implement memory to enable conversational and stateful AI agents.
• Output Parsers: Use Pydantic Output Parsers for structured data extraction.
• Chains & Agents: Build complex chains and custom agents with Python Agents and CSV Agents.
• LangSmith & LCE: Leverage LangSmith and LCE for debugging and monitoring your LLM applications.
• LangGraph Ecosystem: Gain a deep understanding of the LangGraph ecosystem, including MCP (Model Context Protocol).
• Cursor IDE: Explore the Cursor IDE and its composable features.

Key Projects & Concepts:

• Search Agent: Build a search agent with advanced retrieval and RAG, capable of generating responses from Python package documentation and custom data.
• Documentation Helper: Create a chatbot that answers questions using Python package documentation and other data sources.
• Slim ChatGPT Code Interpreter: Develop a lightweight code execution assistant.
• Ice Breaker Agent: An AI agent that scrapes public information from Google, LinkedIn, and Twitter to generate personalized icebreakers.

Course Highlights:

• Up-to-date: Covers the latest LangChain (v1.0+) and LangGraph ecosystem.
• Practical: Focuses on real-world projects and APIs.
• Career-Boosting: Develop in-demand skills for the LLM and GenAI job market.
• Step-by-Step Guidance: Clear, concise instructions for easy learning.
• Flexible: Use your preferred Python IDE (Pycharm is recommended).

Prerequisites: This course is not for beginners. A solid background in software engineering and proficiency in Python are required. The course uses Pycharm IDE, but you can use any editor.

Disclaimer: This course assumes prior knowledge of software engineering and Python.