AWS AI Training covers tools, services, and frameworks offered by Amazon Web Services for building intelligent applications. Gain hands-on experience in machine learning, natural language processing, computer vision, and AI model deployment using AWS SageMaker, Lex, Polly, Rekognition, and more.
Prerequisites
- Basic knowledge of AWS services and cloud computing.
- Familiarity with Python programming.
- Understanding of AI and machine learning fundamentals.
What You Will Learn
- Fundamentals of Artificial Intelligence (AI) and its applications – Core AI/ML concepts, supervised vs. unsupervised learning, neural networks, and real-world industry applications — with a focus on how 2026’s agentic AI era changes how AI is built and deployed.
- Hands-on with AWS AI services: SageMaker, Rekognition, Comprehend, Lex, Polly, Transcribe, Bedrock, Amazon Quick, and Amazon Connect expanded into four agentic AI solutions covering supply chain, hiring, and customer experience.
- Build, train, and deploy AI models with SageMaker – End-to-end model lifecycle on SageMaker from data prep to training to deployment.
- Implement computer vision with Rekognition – Image and video analysis, facial recognition, object detection, and content moderation using Amazon Rekognition.
- Perform NLP tasks with Comprehend – Text classification, entity recognition, sentiment analysis, and key phrase extraction using Amazon Comprehend integrated with Bedrock for generative NLP pipelines.
- Create chatbots with Lex – Design and deploy intelligent chatbots with Amazon Lex.
- Use Polly and Transcribe for speech AI – Text-to-speech and speech-to-text pipelines with Amazon Polly and Transcribe. Includes AgentCore Runtime’s new bidirectional streaming for natural voice conversations.
- Generative AI Development with Amazon Bedrock – Build production-grade GenAI apps using Bedrock’s model library like Claude, Amazon Nova, Meta Llama, Mistral, and more. Covers RAG pipelines, prompt engineering, fine-tuning with Nova Forge, and Amazon Bedrock Managed Agents powered by OpenAI.
- Amazon Nova AI Models – Dedicated module on Amazon’s own model family — Nova Lite, Nova Pro, and Nova Premier
- Amazon Bedrock AgentCore – Build and Deploy AI Agents with the biggest new addition. AgentCore is a platform for building, deploying, and operating AI agents securely
- AgentCore Payments: Autonomous Agent Transactions – AgentCore Payments enables AI agents to autonomously access and pay for APIs, MCP servers, web content, and other agents
- Kiro: Agentic IDE for Developers – Kiro guides developers from prompt to feature with step-by-step guidance
- AWS Trainium3 and AI Infrastructure – Trainium3 UltraServers deliver up to 4.4× more compute performance, 4× greater energy efficiency, and nearly 4× more memory bandwidth than Trainium2
- Amazon S3 Vectors – AI-Native Storage S3 Vectors eliminates the need for a separate vector database for most AI use cases, cutting storage costs by up to 90%.
- Responsible AI practices: ethics, fairness, and data security – Ethics, fairness, data security, and compliance updated for the agentic era.
What’s New in AWS AI (2026)
- Amazon Nova AI Models
- Advanced AI Agents and Automation
- Generative AI Development with Amazon Bedrock
- OpenAI Integration with AWS
- Improved SageMaker AI Capabilities
- New AI Infrastructure and AI Chips
- Next-Generation AI Inference Systems
