This highly-rated course boasts a 0.0-star-star rating from 0 reviews and has successfully guided 1,030 students in mastering Other IT & Software skills. Featuring 8 hour(s) 30 minute(s) of expert-led content delivered in English, this course offers thorough training to enhance your Social Science expertise. The course details were last updated on December 24, 2024. This coupon code is brought to you by Anonymous.
- Expired on February 11, 2025
- Last Update: February 11, 2025
- Price: 94.99 $
About This Course
Master LangChain and build smarter AI solutions with large language model (LLM) integration! This course covers everything you need to know to build robust AI applications using LangChain. We’ll start by introducing you to key concepts like AI, large language models, and retrieval-augmented generation (RAG). From there, you’ll set up your environment and learn how to process data with document loaders and splitters, making sure your AI has the right data to work with.
Next, we’ll dive deep into embeddings and vector stores, essential for creating powerful AI search and retrieval systems. You’ll explore different vector store solutions such as FAISS, ChromaDB, and Pinecone, and learn how to select the best one for your needs. Our retriever modules will teach you how to make your AI smarter with multi-query and context-aware retrieval techniques.
In the second half of the course, we’ll focus on building AI chat models and composing effective prompts to get the best responses. You’ll also explore advanced workflow integration using the LangChain Component Execution Layer (LCEL), where you’ll learn to create dynamic, modular AI solutions. Finally, we’ll wrap up with essential debugging and tracing techniques to ensure your AI workflows are optimized and running efficiently.
What Will You Learn?
How to set up LangChain and Ollama for local AI development
Using document loaders and splitters to process text, PDFs, JSON, and other formats
Creating embeddings for smarter AI search and retrieval
Working with vector stores like FAISS, ChromaDB, Pinecone, and more
Building interactive AI chat models and workflows using LangChain
Optimizing and debugging AI workflows with tools like LangSmith and custom retriever tracing
Course Highlights
Step-by-step guidance: Learn everything from setup to building advanced workflows
Hands-on projects: Apply what you learn with real-world examples and exercises
Reference code: All code is provided in a GitHub repository for easy access and practice
Advanced techniques: Explore embedding caching, context-aware retrievers, and LangChain Component Execution Layer (LCEL)
What Will You Gain?
Practical experience with LangChain, Ollama, and AI integrations
A deep understanding of vector stores, embeddings, and document processing
The ability to build scalable, efficient AI workflows
Skills to debug and optimize AI solutions for real-world use cases
How Is This Course Taught?
Clear, step-by-step explanations
Hands-on demos and practical projects
Reference code provided on GitHub for all exercises
Real-world applications to reinforce learning
Join Me on This Exciting Journey!
Build smarter AI solutions with LangChain and LLMs
Stay ahead of the curve with cutting-edge AI integration techniques
Gain practical skills that you can apply immediately in your projects
Let’s get started and unlock the full potential of LangChain together!
