Hands-On AI: Building LLM-Powered Apps

Focused View

Han-chung Lee

1:16:23

19 View

01 - Introduction

01 - Building apps using large language models.mp4

00:40

02 - 1. LLM The Essentials

01 - Language models and tokenization.mp4

04:53

02 - Large language model capabilities.mp4

01:48

03 - Challenge Introduction to Chainlit.mp4

02:28

04 - Solution Introduction to Chainlit solution.mp4

01:18

05 - Prompts and prompt templates.mp4

03:00

06 - Obtaining an OpenAI token.mp4

01:20

07 - Challenge Adding an LLM to the Chainlit app.mp4

01:31

08 - Solution Adding an LLM to the Chainlit app.mp4

03:20

09 - Large language model limitations.mp4

03:43

03 - 2. Retrieval Augmented Generation

01 - Retrieval augmented generation.mp4

03:30

02 - Search engine basics.mp4

02:32

03 - Embedding search.mp4

03:00

04 - Embedding model limitations.mp4

03:15

05 - Challenge Enabling load PDF to Chainlit app.mp4

00:48

06 - Solution Enabling load PDF to Chainlit app.mp4

05:04

07 - Challenge Indexing documents into a vector database.mp4

01:50

08 - Solution Indexing documents into a vector database.mp4

01:43

09 - Challenge Putting it all together.mp4

01:10

10 - Solution Putting it all together.mp4

03:17

11 - Trying out your chat with the PDF app.mp4

02:15

04 - 3. Prompt Engineering

01 - Prompt engineering basics.mp4

05:19

02 - Challenge Set up prompting.mp4

01:35

03 - Solution Set up prompting.mp4

03:53

04 - Prompt playground for LLM apps.mp4

03:15

05 - Challenge Fixing hallucination via prompting.mp4

01:18

06 - Solution Fixing hallucination via prompting.mp4

07:15

05 - Conclusion

01 - Continue your LLM journey.mp4

01:23

Description

Are you ready to start building applications with large language models (LLMs), but not sure where to begin? This course, which is designed uniquely for beginners with no experience in the LLM space, offers an overview of the fundamentals of LLMs with hands-on challenges to boost your skills along the way.

Explore the essentials of retrieval-augmented generation including search engine basics, embedding model limitations, and how to build a chat-with-PDF application. Along the way, instructor Han Lee shows you how to get up and running with prompt engineering, using the prompt playground for LLM apps.

This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace. Check out the “Using GitHub Codespaces with this course” video to learn how to get started.

More details

User Reviews

Rating

average 0

Total votes0

Focused display

Artificial Intelligence

Han-chung Lee

Instructor's Courses

Linkedin Learning

View courses Linkedin Learning

LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.