Udemy – Mastering Generative AI From Neural Networks To Multi Agents
English | Tutorial | Size: 4.28 GB
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.
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