本講座のレビューに関して記載された記事数の「直近6カ月の推移」を以下のグラフにまとめました。
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COURSE WAS RE-RECORDED and supports- LangChain Version 0.3+
**Ideal students are software developers / data scientists / AI/ML Engineers**
Welcome to the AI Agents with LangChain and LangGraph Udemy course - Unleashing the Power of LLM!
This course is designed to teach you how to QUICKLY harness the power the LangChain library for LLM applications.
This course will equip you with the skills and knowledge necessary to develop cutting-edge LLM solutions for a diverse range of topics.
Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python. I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts .
What You’ll Build: No fluff. No toy examples. You’ll build:
Ice Breaker Agent – An AI agent that searches Google, finds LinkedIn and Twitter profiles, scrapes public info, and generates personalized icebreakers.
Documentation Helper – A chatbot over Python package docs (and any data you choose), using advanced retrieval and RAG.
Slim ChatGPT Code Interpreter – A lightweight code execution assistant.
Prompt Engineering Theory Section
Introduction to LangGraph
Introduction to Model Context Protocol (MCP)
The topics covered in this course include:
AI Agents
LangChain, LangGraph
LLM + GenAI History
LLMs: Few shots prompting, Chain of Thought, ReAct prompting
Chat Models
Open Source Models
Prompts, PromptTemplates, langchainub
Output Parsers, Pydantic Output Parsers
Chains: create_retrieval_chain, create_stuff_documents_chain
Agents, Custom Agents, Python Agents, CSV Agents, Agent Routers
OpenAI Functions, Tool Calling
Tools, Toolkits
Memory
Vectorstores (Pinecone, FAISS, Chroma)
RAG (Retrieval Augmentation Generation)
DocumentLoaders, TextSplitters
Streamlit (for UI), Copilotkit
LCEL
LangSmith
LangGraph
FireCrawl
GIST of Cursor IDE
Cursor Composter
Curser Chat
MCP - Model Context Protocol & LangChain Ecosystem
Introduction To LangGraph
Throughout the course, you will work on hands-on exercises and real-world projects to reinforce your understanding of the concepts and techniques covered. By the end of the course, you will be proficient in using LangChain to create powerful, efficient, and versatile LLM applications for a wide array of usages.
Why This Course?
Up-to-date: Covers LangChain v0.3+ and the latest LangGraph ecosystem.
Practical: Real projects, real APIs, real-world skills.
Career-boosting: Stay ahead in the LLM and GenAI job market.
Step-by-step guidance: Clear, concise, no wasted time.
Flexible: Use any Python IDE (Pycharm shown, but not required).
DISCLAIMERS
Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python.
I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts.
The Ice-Breaker project requires usage of 3rd party APIs-
Scrapin, Tavily, Twitter API which are generally paid services.
All of those 3rd parties have a free tier we will use to create stub responses development and testing.
本コースの特徴を単語単位でまとめました。以下の単語が気になる方は、ぜひ本講座の受講をオススメします。
本講座を受講した皆さんの感想を以下にまとめます。
・【個人開発】LangGraphを使って読書メモからクイズを生成するアプリを作った話[2025-05-11に投稿]
・1週間でLangChainを使えるようになる: Day 1 - LangChainとは[2025-03-20に投稿]