- Fundamentals of AI
- Exploring NN Architectures
- Intro to PyTorch
- Backpropagation
- Intro to PyTorch Lightning, Tensorboard and Gradio
- Advanced Architectures in Convolution & Visualization
- Optimizations
- Data Augmentation
- Residual Connections in CNN and FC
- Unsolved MNIST
- Segmentation Model
- YOLO
- UNETs, Variation AutoEncoders and Applications
- Transformers and Advanced Embedding Techniques
- Encoder Architectures
- BERT
- Masked AutoEncoders
- Vision Transformers
- Decoders
- Generative Pre-trained Transformers
- Training and Fine-tuning LLM (QLoRA)
- CLIP Models and Training
- Generative Art and Stable Diffusion
- Automatic Speech Recognition Fundamentals
- Reinforcement Learning I
- Reinforcement Learning II
- Reinforcement Learning from Human Feeedback, DPO
- Training ChatGPT from scratch
- Training Multimodel GPTs