[2026] Complete AWS Bedrock Generative AI Course + Projects
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Unclaimed ProfileThe AWS Bedrock landscape is evolving rapidly, and Patrik Szepesi's comprehensive course provides developers, cloud architects, and AI enthusiasts with the exact tools needed to master generative AI on AWS. Designed for all levels, this course dives deep into AWS Bedrock, walking students through the creation of advanced multi-agent workflows, real-time voice agents, and sophisticated document chat systems. Throughout the curriculum, you will explore cutting-edge concepts such as short-term and long-term agent memory, Reinforcement Fine-Tuning, and Bedrock Data Automation for extracting key insights from videos, images, and audio files. Students will gain practical, hands-on experience building serverless machine learning applications using the robust AWS serverless stack, including AWS Lambda, API Gateway, S3, and Bedrock AgentCore. Whether you want to deploy production-ready agentic collaborations, design intelligent prompt routing to save on inference costs, or implement security features to identify AI-generated images, this course offers the perfect balance of theory and real-world projects. By the end of this journey, you will confidently build, train, evaluate, and deploy scalable generative AI solutions in the cloud.
About the creator
Patrik Szepesi
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Patrik Szepesi is an experienced cloud engineer and technical educator dedicated to demystifying the world of cloud-based artificial intelligence. With a specialized focus on Amazon Web Services (AWS) and its cutting-edge generative AI capabilities, Patrik bridges the gap between complex machine learning theory and practical, real-world deployment. His professional background spans designing robust cloud architectures and integrating advanced language models into enterprise workflows. As an instructor, Patrik adopts a hands-on, project-driven approach to teaching. He believes that the best way to master technology is by building, which is why his courses are structured around tangible, real-world projects rather than dry…Show more
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Program Overview
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Learning format
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Price may change · updated within 1–2 weeks
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What You'll Learn
- AWS Bedrock
- Learn how to Extract Information from Videos, Images, Audio, and Documents with Bedrock Data Automation
- Create Multi Agentic Workflows on AWS Bedrock
- Add Long Term + Short Term Memory to your Agents
- Generative AI
- Build Serverless Machine Learning applications
- Deploy Your Agents in Production to AWS Bedrock AgentCore
- How to Use Reinforcement Fine Tuning with AWS Bedrock to Train Your Own Models
- Fine Tune LLMs in the cloud
- Build production ready applications with Aws Serverless stack such as Bedrock, Lambda and Api Gateway and S3
- Train and Evaluate LLMs with your own custom data
- Building Production Grade Voice agents on AWS
- Understand short-term vs long-term agent memory and when to use each
- AWS Bedrock Pricing
- Summarise your meeting notes in a matter of seconds
- Serverless Architecture
- API Gateway
- AWS Bedrock 2026 Updates
- Deploy Multi Agentic Workflows with Streamlit
- Intelligent Prompt Routing, and How to save Time on Money on your LLM Inferences
- Image Generation
- Text Summarisation with NLP
- Text Creation through NLP
- Stability AI and diffusion models for image generation
- Use lifecycle hooks to load and save agent memory automatically
- Anthropic AI
- Learn How to Build true Bidirectional Voice Agents on AWS
- Connect your data in S3 with AWS Bedrock
- Set up Lambda Layers
- Evaluate your LLMs with AWS Bedrock Evaluator
- Prompt Management, Version Control, Prompt Promotion
- Build a web search agent with AWS Strands and DuckDuckGo
- How to Write Good Prompts with Bedrock
- Use Agent Collaborations for tasks
- Chat with Documents
- Using AWS Batch Inference to Get Cheaper Inference on your LLM Calls
- Identify if an Image Was Created with AI
- Prompt Optimization
- Create Bedrock Data Automation Blueprints for your Custom Domain
- Building Interruptible Voice Agents
- Add long-term memory with semantic and preference strategies
- Deploy agents to production using Bedrock AgentCore Runtime
- Implement short-term memory for conversation tracking
- AWS Strands Framework
Best For
- Cloud developers and AWS architects aiming to integrate Generative AI into serverless architectures.
- Engineers who need to build and deploy production-ready AI agents using AWS Bedrock and AgentCore.
- AI enthusiasts looking for hands-on experience with advanced workflows like multi-agent collaboration and voice agents.
- Professionals seeking to master cost-effective LLM deployment through prompt routing and batch inference.
Not For
- Absolute beginners with no prior experience in cloud computing or basic AWS services.
- Data scientists looking for deep mathematical theory of transformer architecture rather than practical implementation.
- Developers who strictly want to build local AI models rather than scalable, serverless cloud solutions.
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