What Will You Learn?
• Models, Prompts and Parsers
• memories to store conversations and manage limited context space
• Chains: creating sequences of operations
• Question Answering over Documents: apply LLMs to your proprietary
data and use case requirements
• Agents: explore the powerful emerging development of LLM as reasoning agents.
About This Course
Provider: .deeplearning.ai
Format: Online
Duration: 1 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: LangChain for LLM Application Development is a beginner-friendly course. Basic Python knowledge will help you get the most
out of this course.
Course Prerequisites: NA
Assessment and Certification: NA
Instructor: Harrison Chase,Andrew Ng
Key Topics: LLM,Models, Prompts and Parsers,Chains
Topic Covered:
- What is LLM?
- - LangChain framework
- - Models, Prompts and Parsers: calling LLMs, providing prompts and parsing the response
- - Memories for LLMs: memories to store conversations and manage limited context space
- - Chains: creating sequences of operations
- - apply LLMs to your proprietary data and use case requirements
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