Mastering Generative AI From Neural Networks to Multi-Agents

Learn the fundamentals of LLMs, Transformers, AI Agents, Multi-Agents, RAG

Master Generative AI from the ground up in this comprehensive masterclass that takes you from core machine learning concepts to building production-ready AI applications. Whether you're a software engineer, data scientist, or tech professional looking to stay ahead of the AI revolution, this course provides everything you need to become a Generative AI expert.

Core Foundations:

• Deep dive into Machine Learning, Neural Networks, and Deep Learning fundamentals

• Understand embeddings, transformers, and diffusion models that power modern AI

• Learn how foundation models like GPT, Claude, and Stable Diffusion actually work

Natural Language Processing Mastery:

• Build and fine-tune Large Language Models (LLMs) for conversation and text generation

• Master tokenization, text classification, topic modeling, and named entity recognition

• Understand evaluation metrics and benchmarks used by industry leaders

• Implement supervised fine-tuning for specialized AI applications

Image Generation & Computer Vision:

• Create stunning images using text-to-image and image-to-image models

• Master image editing, inpainting, and style transfer techniques

• Fine-tune image generation models for custom use cases

Advanced Model Customization:

• Master prompt engineering and in-context learning strategies

• Build Retrieval Augmented Generation (RAG) systems that ground AI in your data

• Implement cutting-edge GraphRAG and StructRAG architectures

• Apply Parameter-Efficient Fine-Tuning (PEFT) and LoRA techniques

• Train models using Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO)

• Optimize models through knowledge distillation

  
  

Agentic AI & Advanced Orchestration:

• Understand the fundamentals of AI agents and agentic reasoning

• Master the ReAct (Reasoning and Acting) framework for tool-using agents

• Design and implement multi-agent systems with role specialization

• Build agent topologies: sequential, hierarchical, and collaborative patterns

• Implement automatic handoffs and agent coordination strategies

• Create agents that can plan, reason, and execute complex multi-step tasks

Hands-On Learning Experience

This isn't just theory—you'll build real AI applications through 8 comprehensive labs that progressively build your skills:

Lab 1: Neural Network Fundamentals & Transfer Learning Build an image classifier from scratch, understand training and inference pipelines, and leverage transfer learning with ResNet for state-of-the-art performance.

Lab 2: AWS & Generative Image Creation Set up your AWS environment, work with Amazon Bedrock, and create and edit stunning images using Amazon Nova models—your gateway to cloud-based AI.

Lab 3: Embeddings & Vector Search Master embedding models with HuggingFace, build a production-ready RAG system, and implement efficient vector databases with IVF and HNSW indexing strategies.

Lab 4: Advanced LLM Techniques Work with Amazon Bedrock LLMs for real-world tasks: prompt engineering, text classification, document summarization, and creative content generation.

Lab 5: Conversational AI Build an intelligent chatbot using Amazon Bedrock and Gradio with memory management and multi-turn conversation capabilities.

Lab 6: Custom AI Agents Implement your own ReAct (Reasoning and Acting) agent from scratch with Amazon Bedrock, understanding how agents think and use tools.

Lab 7: Full-Stack Agentic Application Create a production-ready agentic chatbot using the Strands SDK, FastAPI backend, and Amazon Bedrock—ready for real-world deployment.

Lab 8: Multi-Agent Systems Build sophisticated multi-agent systems with the Strands SDK featuring automatic handoffs, agent collaboration, and coordinated problem-solving.