English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 5h 21m | 918 MB
This course provides a comprehensive yet concise introduction to LangChain, a powerful framework for large language model (LLM) applications. Starting with the basics of LLMs, instructor Harpreet Sahota explores the key features and capabilities of LangChain, showing you how to integrate it with various systems and gain hands-on experience in building practical applications. Whether you’re a seasoned developer or a beginner, this course will equip you with a solid foundation in LangChain, setting the stage for more advanced topics and applications.
Table of Contents
Introduction
1 Create powerful LLM driven applications
Introduction to Language Models
2 What are language models
LLMs and Text Generation
3 How do language models generate text
4 Base LLMs vs. instruction-tuned LLMs
5 Training, fine-tuning, and in-context learning
6 Prompt engineering
Components of LangChain
7 What is LangChain
8 LangChain overview
9 Model IO Interface with language models
10 Retrieval Interface with application-specific data
11 Chains Construct sequences of calls
12 Agents Let chains choose tools based on high-level directives
13 Memory Persist application state between runs of a chain
Basics of Prompting
14 Prompt basics
15 Principles and tactics for prompting
Prompt Templates Deep Dive
16 Introduction to prompt templates
17 Multi-input prompt templates
18 Chat prompt template
19 Serializing prompts
20 Zero-shot prompts
21 Custom prompt templates
22 Prompt pipelining
23 Chat prompt pipelining
24 Prompt composition
25 Few-shot prompt templates
26 Few-shot prompt templates for chat
27 Introduction to example selectors
28 Length-based example selector
29 Max marginal relevance example selector
30 N-gram overlap example selector
31 Semantic similarity example selector
32 Partial prompt templates
Prompting Techniques
33 Chain of thought
34 Self-consistency
35 Self-ask
36 ReAct
37 RAG
38 FLARE
39 Plan and execute
Prompt Management a.k.a. PromptOps
40 Prompt management
41 LangSmith
42 LangSmith walkthrough
43 Prompt versioning in LangSmith
44 LangSmith deep dive
45 Managing prompt length for agents
The LLM Landscape
46 Applications of language models
47 The LLM landscape
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