English | Size: 1.8 GB
Genre: eLearning
Elevate Your RAG Applications to the Next Level
What you’ll learn
Learn LangChain Expression Language (LCEL)
Master advanced RAG techniques using the LangChain framework
Evaluate RAG pipelines using the RAGAS framework
Apply NeMo Guardrails for safe and reliable AI interactions
What to Expect from This Course
Welcome to our course on Advanced Retrieval-Augmented Generation (RAG) with the LangChain Framework!
In this course, we dive into advanced techniques for Retrieval-Augmented Generation, leveraging the powerful LangChain framework to enhance your AI-powered language tasks. LangChain is an open-source tool that connects large language models (LLMs) with other components, making it an essential resource for developers and data scientists working with AI.
Course Highlights
Focus on RAG Techniques: This course provides a deep understanding of Retrieval-Augmented Generation, guiding you through the intricacies of the LangChain framework. We cover a range of topics from basic concepts to advanced implementations, ensuring you gain comprehensive knowledge.
Comprehensive Content: The course is designed for developers, software engineers, and data scientists with some experience in the world of LLMs and LangChain. Throughout the course, you’ll explore:
- LCEL Deepdive and Runnables
- Chat with History
- Indexing API
- RAG Evaluation Tools
- Advanced Chunking Techniques
- Other Embedding Models
- Query Formulation and Retrieval
- Cross-Encoder Reranking
- Routing
- Agents
- Tool Calling
- NeMo Guardrails
- Langfuse Integration
Additional Resources
- Helper Scripts: Scripts for data ingestion, inspection, and cleanup to streamline your workflow.
- Full-Stack App and Docker: A comprehensive chatbot application with a React frontend and FastAPI backend, complete with Docker support for easy setup and deployment.
- Additional resources are available to support your learning.
Happy Learning! 🙂
Who this course is for:
- Software Engineers and Data Scientists with Experience in Langchain who want to bring RAG applications to the next level
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