• What is Generative AI?
• Generative vs. Discriminative models
• Why Generative models?
• Encoder-Decoder design pattern
• GenAI modalities mappings

• Unimodal mappings: Txt2txt and Language models
• Statistical Language Models (SLM)
• Neural Language Models (NLM) – Char & Word level
• SLM and NLM in Python and Keras
• Seq2seq models
• Seq2seq + Attention models
• Transformers
• Huggingface Transformer Pipeline
• Large-Scale Language Models (LLM) – Transfer Learning in NLP
• Pre-trained Transformers
• GPT
• ChatGPT
• OpenAI API
• GPT-3 Fine Tuning
• GPT-3 Chatbot
• ChatGPT Clone in Google Colab & Streamlit

• Img2Img Encoder-Decoder
• Auto Encoder (AE)
• AE Visualization
• Variational Auto Encoder (VAE)
• Conditional VAE
• Coding AE in Keras
• Generative Adversarial Nets (GANs)
• Generating images from GANs
• Training GANs
• Coding GAN training in Keras
• DCGAN
• Conditional GANs
• AttributeGAN
• How Good are GANs today?
• Domain adaptation with pix2pix and CycleGAN

• The GIST of LLMs
• What is a Prompt? Composition of a formal prompt
• Zero Shot Prompting
• Few Shot Prompting
• Chain of Thought Prompting
• ReAct

Creating your API Key for Open AI

• What is LangChain?
• LangChain Modules : Models, Prompts, Chain
• LangChain Modules : Tools and Agents
• Langchain Modules : Memory
• Langchain Modules : Document Loaders and Indexes
• Building a Chatbot on your custom csv data

• The Power of Attention Mechanisms
• Unraveling Encoder-Decoder Architectures
• Demystifying Transformers
• Learn and Understand Transformers
• Mastering Scaled Dot Product Attention 
• Delving into Multi-Headed Attention
• Unlocking Transfer Learning Potential 
• GPT Pre-Training Strategies and Techniques
• Optimizing GPT Pre-Training for Performance
• Mastering Few-Shot Learning with GPT
• Advanced Approaches in Few-Shot Learning
• Exploring Stylistic Completion with GPT: An Introduction
• Advanced Techniques in Stylistic Completion with GPT