LangChain- Develop LLM powered applications with LangChain

Welcome to first LangChain Udemy course - Unleashing the Power of LLM!

This comprehensive 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.

In this course, you will embark on a journey from scratch to building a real-world LLM powered application using LangChain.

We are going to do so by build 3 main applications:

1. Ice Breaker- LangChain agent that given a name, searches in google to find Linkedin and twitter profiles, scrape the internet for information about a name you provide and generate a couple of personalized ice breakers to kick off a conversation with the person.
2. Documentation Helper- Create chatbot over a python package documentation. (and over any other data you would like)
3. A slim version of ChatGPT Code-Interpreter

The topics covered in this course include:

1. LangChain
2. History
3. LLMs: Few shots prompting, Chain of Thought, ReAct prompting
4. Chat Models
5. Prompts, PromptTemplates
6. Output Parsers
7. Chains: SequentialChain, LLMChain, RetrievalQA chain
8. Agents, Custom Agents, Python Agents, CSV Agents, Agent Routers
9. OpenAI Functions
10. Tools, Toolkits
11. Memory
12. Vectorstores (Pinecone, FAISS)
13. DocumentLoaders, TextSplitters
14. Streamlit (for UI)