Basics of Practical GenAI

This is part 1 of the Practical GenAI Sequel.

The objective of the sequel is to prepare you to be a professional GenAI engineer/developer. I will take you from the ground-up in the realm of LLMs and GenAI, starting from the very basics to building working and production level apps.

The spirit of the sequel is to be “hands-on”. All examples are code-based, with final projects, built step-by-step either in python, Google Colab, and deployed in streamlit.

By the end of the courses sequel, you will have built chatgpt clone. We will cover prompt engineering approaches, and use them to build custom apps, that go beyond what ChatGPT knows. We will use OpenAI APIs, LangChain and many other tools. We will build together different applications using streamlit as our UI and cloud deployment framework. Streamlit is known of its ease of use, and easy python coding.

This course is for:

An entrepreneur with good developer background can benefit from the course in proofing his concept (PoC)

A developer, with good AI background, can enrich his capabilities to integrate GenAI in his apps.

And finally the GenAI engineer, which should be able to cover all the aspect of GenAI; either theoritically or practically, and navigate through the different requirements and issues that might be encountered while building GenAI apps.

This leads us to talk a bit about “What is a GenAI engineer?”