Generative AI

Deep Learning Foundations

Introduction to Generative AI

Neural Network Fundamentals

Training Optimization

Transformers and Attention

Generative Architectures

Autoencoders and VAEs

GAN Fundamentals

Vision Transformers

Diffusion Models

Diffusion Fundamentals

Advanced Diffusion

Diffusion Image Generation

Large Language Models

Tokenization and Embeddings

LLM Fundamentals

LLM Scaling and Capabilities

LLM Model Types

Training LLMs

Data Preparation

Training Paradigms

Fine-tuning Techniques

Distributed Training

Alignment and RLHF

Using LLMs

Prompt Engineering

Inference and Generation

Text Applications

Conversational AI

Visual and Audio AI

Image Editing

Multimodal AI

Audio Generation

Advanced Applications

Video and 3D

Code Generation

RAG Systems

Structured Output

Agentic AI

Agentic AI Fundamentals

Building AI Agents

Advanced Agent Systems

Model Optimization

Model Compression

Inference Optimization

Model Evaluation

Reliability and Grounding

Safety and Ethics

AI Ethics

AI Security

Interpretability

Legal and Licensing

Synthetic Media