Getting started with AWS for Machine Learning and Generative AI

Join us for a hands-on, beginner-friendly session designed to kickstart your journey into the world of Machine Learning and Generative AI using AWS. Discover how you can leverage Amazon SageMaker and Amazon Bedrock to build powerful AI solutions with Large Language Models (LLMs), intelligent agents, and Model Customization Pipelines (MCP). Whether you're a developer, data enthusiast, or business decision-maker, this session will guide you through real-world examples, key tools, and practical steps to build your first ML and GenAI workflows on AWS.
Webinar Lead: Bismillah Kani, AI Scientist, AWS Evangelist, Mentor - RACE
https://www.linkedin.com/in/bismillah-kani-49a31115/

Registration Form: https://forms.office.com/r/nVQHLBumCS

Date and Time: May 30th 6.30 pm to 7.30 pm
Who Can Attend:

• Tech professionals and developers new to AWS ML/AI
• Data scientists exploring GenAI tools
• Product managers and startup teams building AI features
• Students and educators in AI/ML disciplines
• Business leaders curious about Generative AI on cloud platforms

Key Takeaways:

• Understand the role of Amazon SageMaker in ML lifecycle management
• Explore how Amazon Bedrock enables easy access to foundation models
• Learn what LLMs, Agents, and MCP mean in an AWS context
• Discover quick-start templates and workflows to launch your first AI solution
• Get insights into future trends in AI cloud integration

Tools & Services Covered:

• Amazon SageMaker (for ML model training, tuning, deployment)
• Amazon Bedrock (for generative AI and foundation models access)
• LLMs on AWS (e.g., Anthropic Claude, Mistral, Meta Llama)
• Agents for Bedrock (to automate multi-step tasks using natural language)
• Model Context Protocol (MCP)