Generative AI Starter – From Fundamentals to Real-World Projects

Description

✅ What You Will Learn

📌 Module 1 – Core Foundations

• Introduction to Neural Networks

• Loss Functions & Activation Functions in Depth

• Mathematical Foundations & Convolution Operations

📌 Module 2 – Practical Deep Learning

• Data Preprocessing with Model Code Examples

• CNNs & Autoencoders

• Introduction to GANs & Variational Autoencoders (VAEs)

• Types of Layers & Deep Generative Models

📌 Module 3 – Sequential & Attention-Based Models

• RNNs & LSTMs

• Transformer Architecture Deep Dive

📌 Module 4 – Model Optimization & Fine-Tuning

• Fine-Tuning Techniques for LLMs

• Fine-Tuning with Unsloth

• Knowledge Distillation

• Model Compression

📌 Module 5 – AI Tools & Frameworks

• LangChain & LangGraph

• Vector Databases & RAG (Retrieval-Augmented Generation)

• Streamlit App Development

• MCP & VAEs in Practice

📌 Module 6 – Modern AI Ecosystem

• Ollama & DeepSeek Integration

• Diffusion Models Overview

• Prompt Engineering Essentials

📌 Module 7 – Capstone Projects

• End-to-End Generative AI Applications

• Deploying AI Apps for Real-World Use

👤 Who Is This Course For?

• Beginners in AI & Machine Learning

• Developers wanting to transition into AI application building

• Professionals exploring Generative AI tools & workflows

• Students preparing for AI-focused career