Tutorials > Mastering Generative Ai From Neural Networks To Multi-Agents

Mastering Generative Ai From Neural Networks To Multi-Agents

Date: 2 October 2025 | Posted by: 0nelove

Mastering Generative Ai From Neural Networks To Multi-Agents
Published 10/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 8h 29m | Size: 4.27 GB
Learn the fundamentals of LLMs, Transformers, AI Agents, Multi-Agents, RAG
What you'll learn

Learn the fundamentals of Machine Learning, Deep Learning and Generative AI
How to create, train and run Deep Neural Networks
What are the building blocks of a LLM: Tokenization, Pre-Training, SFT and RLHF
Customization strategies for LLMs with Fine-Tuning, RAG and Prompt Engineering
Building AI Agents with ReAct and Strands SDK
Fundamentals of NLP to classify documents, extract entities and intelligent document processing
Using AI to edit and create images with Transformer based Models
Create GenAI architectures with Amazon Bedrock
Build AI Agents with Amazon Bedrock and Strands SDK
Create Multi-Agentic Architectures and differentiate between Multi-Agent Topologies
Requirements
No programming necessary you will be guided through all steps
Python and Computer Science experience helpful
You can run the course on your own laptop or on SageMaker Studio Labs (free) to lower hardware barrier
Description
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 fundamentalsUnderstand embeddings, transformers, and diffusion models that power modern AILearn how foundation models like GPT, Claude, and Stable Diffusion actually workNatural Language Processing Mastery:Build and fine-tune Large Language Models (LLMs) for conversation and text generationMaster tokenization, text classification, topic modeling, and named entity recognitionUnderstand evaluation metrics and benchmarks used by industry leadersImplement supervised fine-tuning for specialized AI applicationsImage Generation & Computer Vision:Create stunning images using text-to-image and image-to-image modelsMaster image editing, inpainting, and style transfer techniquesFine-tune image generation models for custom use casesAdvanced Model Customization:Master prompt engineering and in-context learning strategiesBuild Retrieval Augmented Generation (RAG) systems that ground AI in your dataImplement cutting-edge GraphRAG and StructRAG architecturesApply Parameter-Efficient Fine-Tuning (PEFT) and LoRA techniquesTrain models using Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO)Optimize models through knowledge distillationAgentic AI & Advanced Orchestration:Understand the fundamentals of AI agents and agentic reasoningMaster the ReAct (Reasoning and Acting) framework for tool-using agentsDesign and implement multi-agent systems with role specializationBuild agent topologies: sequential, hierarchical, and collaborative patternsImplement automatic handoffs and agent coordination strategiesCreate agents that can plan, reason, and execute complex multi-step tasksHands-On Learning ExperienceThis 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.
Who this course is for
Tech and Business people interested to improve their career in AI space
Students who want to learn the gist of GenAI and Agentic AI to succeed in career entry
Software Developers, Machine Learning Engineers, Data Scientists
Beginner in Cloud who want to learn using Amazon Bedrock and Strands SDK to build Agentic and GenAI solutions

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