The Full Applied GenAI Curriculum

Python Crash Course I

· Python fundamentals

· Experience writing simple Python programs

Python Crash Course II

· Jupyter Notebooks and Google Colab

· Python Libraries for Machine Learning

· Hands-on with Large Language Models

· Accessing popular foundation models via their APIs

· Working with open-source models via Huggingface Transformers

· Working with Stable Diffusion, LoRA

Gen AI Background

· Overview of Generative AI

· Applications of Generative AI

· Recent History of Generative AI

· Methods for Evaluating Generative AI Models

· Ethical Considerations in Generative AI

Neural Networks Background

· Architecture of feedforward neural networks

· Activation functions

· Training neural networks

· Recurrent Neural Networks (RNNs)

· Convolutional Neural Networks (CNNs)

Deep Dive into LLMs

· Probabilistic language models

· The Transformer Architecture

· Scaling Laws

Building Applications with LLMs

· Retrieval-augmented generation (RAG)

· Agents

· LangChain as a toolkit for LLM applications

Training LLMs

· Pretraining LLMs

· Fine-tuning LLMs and LoRA

· Instruction Tuning

· Learning from Preferences (RLHF and DPO)

GenAI for Images

· Diffusion Process (DDPM) and Stable Diffusion

· Latent Diffusion

· Fine-tuning diffusion models and LoRA (Low-Rank Adaptation of Large Language Models)

· Visual Transformers and applications

GenAI for Audio

· Overview of Text-to-Speech Synthesis: Waveform Generation techniques

· Creating New Music and Sounds with WaveNet and GANs

· Voice Models and Architecture: Vocoders, Tacotron, etc.

· Integrating Voice with LLMs

Hands-On Project

· Create LLM-based applications