Next-Generation Amazon SageMaker - The Center for Data, Analytics and AI

Overview

Discover how Amazon SageMaker's next-generation platform unifies data, analytics, and AI capabilities, featuring a demonstration of SageMaker Unified Studio and its implementation for Olympics.com 2028.

Syllabus

• Introduction to Amazon SageMaker
Overview of Amazon SageMaker capabilities
Key benefits of using SageMaker for AI and ML projects
• Understanding the Next-Generation SageMaker Platform
Overview of advancements in the next-generation SageMaker
Integration with AWS data and analytics services
• Unifying Data, Analytics, and AI
Techniques for data preparation and feature engineering
Advanced analytics with SageMaker
Building and training machine learning models
• SageMaker Unified Studio
Key features of the SageMaker Unified Studio
Navigating the Studio interface
Orchestrating end-to-end machine learning workflows
• Demonstrating Use Case: Olympics.com 2028
Case study: Implementing SageMaker for Olympics.com
Data management and integration strategies
Model deployment and monitoring
• Hands-On Workshop
Lab exercises with SageMaker Studio
Data preparation and feature engineering tasks
Building, training, and deploying models
• Best Practices and Optimization
Cost optimization strategies for SageMaker
Security and compliance considerations
Performance tuning and scalability in SageMaker
• Conclusion and Future Trends
Summary of key learnings
Emerging trends and innovations in AI on SageMaker
Resources for continued learning and exploration
• Q&A and Feedback

Subjects

Programming