Hands-On AI: Building Your First LLM-Powered App

1h 14mBeginner2025-08-26

Authors

Han-chung Lee

Course details

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 prompt engineering techniques, including strategies for context engineering to effectively manage and optimize the input provided to LLMs and monitor their insights through observability tools like LangSmith.

Skills covered

TelecommunicationsProgramming FoundationsFull-Stack Web DevelopmentGenerative AIArtificial Intelligence FoundationsPythonProjectArtificial Intelligence (AI)Web DevelopmentNetwork and System AdministrationOpen SourceSoftware Development

Concepts

0. Introduction

01 - Building apps using large language models (LLMs)

1. LLM - The Essentials

02 - Language models and tokenization
03 - LLM capabilities
04 - Challenge - Introduction to Streamlit
05 - Solution - Introduction to Streamlit solution
06 - Prompts and prompt templates
07 - Obtaining an OpenAI token
08 - Challenge - Adding an LLM to the Streamlit app
09 - Solution - Adding an LLM to the Streamlit app
10 - Limitations of LLMs

2. Retrieval-Augmented Generation (RAG)

11 - Introducing RAG
12 - Search engine basics
13 - Embedding search
14 - Embedding model limitations
15 - Challenge - Enabling PDF uploads in the Streamlit app
16 - Solution - Enabling PDF uploads in the Streamlit app
17 - Challenge - Indexing documents into a vector database
18 - Solution - Indexing documents into a vector database
19 - Challenge - Putting it all together
20 - Solution - Putting it all together

3. Prompt Engineering

21 - Prompt engineering basics
22 - Challenge - Set up prompting and LangSmith
23 - Solution - Set up prompting and LangSmith
24 - Challenge - Deploying your app on Hugging Face
25 - Solution - Deploying your app on Hugging Face

Conclusion

26 - Continue your LLM journey