Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 20 Minute(s)
Language
English
Taught by
David Armendáriz
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
Master AI Agents with OpenAI, LlamaIndex, Pinecone & Streamlit. Build an interactive AI agent step by step.
Are you ready to dive into the world of AI and create powerful agents using cutting-edge tools? This course is designed to take you from zero to hero in building intelligent AI agents with OpenAI, LlamaIndex, Pinecone, and Streamlit. Whether you're a beginner exploring AI or a seasoned developer looking to expand your skills, this course offers everything you need to build interactive, real-world AI applications.
What You'll Learn:
How to use OpenAI's API to generate intelligent responses.
Building and managing knowledge indexes with LlamaIndex.
Storing and retrieving vector embeddings with Pinecone for efficient AI searches.
Creating interactive user interfaces for your AI agents with Streamlit.
Best practices for integrating these tools to build scalable AI solutions.
Why Take This Course?
The demand for AI-driven applications is skyrocketing, and understanding how to create AI agents is a game-changing skill. This course provides practical, hands-on experience with real-world use cases. By the end, you'll have built a fully functional AI agent ready to deploy and showcase.
Who This Course Is For:
Developers and engineers interested in AI and machine learning.
Data scientists looking to explore AI-driven tools.
Entrepreneurs and innovators eager to build AI-powered applications.
Students and professionals seeking hands-on experience in AI development.
Join now and unleash the potential of AI agents in your projects!
Course Content
- 6 section(s)
- 25 lecture(s)
- Section 1 Introduction
- Section 2 Tools
- Section 3 Building the agent
- Section 4 Refactoring the code
- Section 5 Getting the index in Pinecone and the deploying the app
- Section 6 Conclusion
What You’ll Learn
- Learn how to combine external data sources with AI to build advanced question-answering systems
- Gain hands-on experience in building custom AI agents using LlamaIndex.
- Understand how to generate and utilize embeddings with text-embedding-3-large for efficient data retrieval.
- Create scalable, intelligent systems capable of retrieving relevant information in real-time.
Skills covered in this course
Reviews
-
TTheodore Wong
This course is good for a moderately experienced Python programmer who is looking for an express introduction to basic LLM/chatbot concepts and tools. Certainly, I personally feel that I have enough knowledge now to assemble a quick-and-dirty RAG chatbot. I feel like the instructor would have benefited from scripting the class in advance of recording, as some of the Python code raised exceptions "live" during the video that the instructor (to be fair) fixed immediately.
-
EEric Bell
I'd like to have access to a GitHub repo with all the source in it for troubleshooting purposes. As I follow along and enter all the code, when there are problem it's good for me to figure them however I'd like to be able compare mine version to yours.
-
FFrédéric CERDAN
I expected more complex agent
-
CCarlos Huamanchumo
Very well explained, I love it
