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Building LLM-Powered Apps course

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Weights & Biases | 29 videos | Updated 2 years ago
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With Building LLM-Powered Apps course you will learn how to build LLM-powered applications using LLM APIs, Langchain and W&B Prompts. This course will guide you through the entire process of designing, experimenting, and evaluating LLM-based apps. 3 videos featured in this playlist are part our the course. To complete the course and receive your free certificate head to wandb.me/LLM-course-YT !

2:41

Kickstart Your Journey in LLM-Powered App Development: Chapter 1

2:43

Your Guide to Discord's GPT-4 Wandbot: Chapter 2

1:54

Navigating W&B Prompts Tracer for LLMs - Deep Dive into Analysis & Tracking: Chapter 3

5:16

LLM Foundations: Understanding Tokenization & Training: Chapter 4

4:50

Hands-On LLM Experiments with Jupyter & OpenAI API: Chapter 5

2:29

Sampling Methods in LLMs Explained: Chapter 6

5:46

Deep Dive into LLM Sampling Techniques: Chapter 7

5:42

Mastering OpenAI Chat API in LLM Applications: Chapter 8

2:07

Mastering Prompt Engineering for LLMs: Chapter 9

11:14

Advancing Prompt Engineering Techniques in LLMs: Chapter 10

7:16

Crafting Complex Level 5 Prompts for GPT-4: Chapter 11

2:49

Data Analysis & Refinement in LLMs: Chapter 12

3:36

Advanced Architectures for LLM Apps - Integrating Embeddings: Chapter 14

5:16

Mastering Embedding Stores & Vector Databases in LLM Apps with Anton Troynikov: Chapter 15

2:39

Deep Dive into Document Parsing Mastery: Chapter 16

9:11

Implementing LLM QA Chains: Chapter 17

6:38

LLM Chat Interface & Document Ingestion: Chapter 18

9:14

Building Web Chatbots with LLM: Chapter 19

3:14

Advanced LLM App Evaluation: Chapter 20

6:04

LLM App Enhancement Strategies: Chapter 21

3:34

Advanced LLM Evaluation Techniques: Chapter 22

3:08

LLM Result Analysis Explained: Chapter 23

11:47

Controlling LLM Outputs with Shreya Rajpal: Chapter 24

11:36

Unlock AI Security Essentials: Chapter 25

1:53

Mastering Blockchain Integration: Chapter 26

2:11

Final LLM Course Insights: Chapter 27

11:40

Controlling LLM outputs for practical applications

11:29

LLM Safety and LLM Prompt Injection

5:08

Comprehensive overview of Vector Databases