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Implement user-level access control for multi-tenant ML platforms on Amazon SageMaker AI

In this course, you will learn how to implement user-level access control for multi-tenant machine learning platforms on Amazon SageMaker AI. You will explore attribute-based access control (ABAC) patterns that enable granular user access control while minimizing the proliferation of AWS Identity and Access Management (IAM) roles.

Unlocking Telecom Innovation with AWS: NFVI, CNFI, and Generative AI Use Cases

Over the last decade, the telecom industry has witnessed rapid innovation, driven by the evolution of network technologies from 3G and 4G to LTE and now 5G. Both telecom vendors and operators have significantly expanded the potential of connected devices and services. This session will provide participants with a comprehensive understanding of the telecom ecosystem and how AWS services can be leveraged to support cloud-native telecom workloads. We will explore how Network Function Virtualization Infrastructure (NFVI) and Containerized Network Function Infrastructure (CNFI) can be deployed and optimized on AWS to deliver operational efficiency, resiliency, security, performance, and cost-effectiveness. The session will highlight cutting-edge Generative AI use cases tailored for telecom operators, demonstrating how AI can further transform network operations, customer engagement, and service innovation.

Amazon Connect AI Workforce Optimization

Overview of Amazon Connect's AI-driven workforce optimization tools, including forecasting, scheduling, and quality management. Covers how machine learning improves staffing accuracy and how AI evaluation forms automate agent performance reviews.

Building Safe Generative AI Applications with Amazon Bedrock Guardrails

Introduction to Amazon Bedrock Guardrails, including configuring content filters, word filters, and PII redaction policies to mitigate harmful or off-policy outputs from foundation models.

Domain 2 Review: AWS Certified AI Practitioner (AIF-C01 - English)

Review of Domain 2 (Fundamentals of Generative AI) for the AWS Certified AI Practitioner (AIF-C01) exam. Covers foundation models, the FM lifecycle, customization approaches such as RAG and fine-tuning, and supporting AWS services.

Evaluating generative AI models with Amazon Nova LLM-as-a-Judge on Amazon SageMaker AI

Hands-on coverage of using Amazon Nova as an LLM-as-a-Judge on Amazon SageMaker AI to evaluate generative model outputs. Covers rubric design, automated scoring, and integrating evaluations into model selection workflows.

Monitoring and Troubleshooting Generative AI Applications on AWS

Patterns for monitoring and troubleshooting generative AI applications on AWS, covering token and latency metrics, prompt and completion logging, evaluation pipelines, and integrating signals into CloudWatch and observability tooling.

AI Agent Guardrails for Production on AWS | Databases for AI

Most teams find out where the autonomy line is after something goes wrong. This stream is about how to draw that line first. The problem isn't the model — it's that nobody defined the rules of engagement before deployment.

Amazon Connect AI Agent Capabilities

Overview of AI agent capabilities in Amazon Connect, including generative-AI-powered virtual agents that automate customer interactions across voice and chat. Covers configuration, knowledge sources, and handoff between AI and human agents.

An Executive's Guide to Generative AI Success

Executive-oriented overview of how to drive generative AI success in an organization. Covers strategy, use case selection, talent and operating model considerations, risk management, and measuring business value.

Automating with AI/ML for Small Business Owners

Practical introduction to AI and machine learning for small business owners. Covers everyday automation use cases, available AWS AI services, and how to evaluate cost, complexity, and value when adopting AI tools.

Building a Generative AI-Ready Organization

Organizational readiness guide for adopting generative AI, covering operating model, talent and skills, data foundations, governance, and the change management practices required to scale GenAI across an enterprise.

Empower Search with AI using Amazon OpenSearch Service

Demonstrates adding AI-powered search to applications with Amazon OpenSearch Service, including semantic and hybrid search, neural search pipelines, and integration with embedding models hosted on Amazon Bedrock or SageMaker.

Generative AI Workloads on AWS AI Chips - Trainium and Inferentia

Covers running generative AI workloads on AWS Trainium and Inferentia, including the Neuron SDK, model compilation, distributed training on Trn1/Trn2, and inference on Inf2 instances for cost-effective LLM deployment.

Getting Started with Amazon Augmented AI

Introduction to Amazon Augmented AI (A2I), the service for adding human review to machine learning predictions. Covers worker task templates, flow definitions, and integrating A2I with services like Textract and Rekognition.

Introduction to AWS AI Factories

Introduction to AWS AI Factories, fully managed AWS AI infrastructure deployed inside customer data centers. Covers reference architectures, integration with Amazon Bedrock and SageMaker, and use cases for sovereign and on-premises AI workloads.

Planning a Generative AI Project

Practical guide to planning a generative AI project, covering use case framing, data and model strategy, success metrics, risk and compliance considerations, and the team and operating model needed for delivery.

Pricing and Packaging Generative AI in SaaS

Guidance for SaaS providers on pricing and packaging generative AI features, covering cost-of-goods modeling, value-based pricing strategies, metering, and balancing margin with adoption when shipping AI capabilities.

Sustainability Strategies with Generative AI

Examines how generative AI can support sustainability initiatives, and how to design and operate generative AI workloads on AWS in line with the sustainability pillar of the Well-Architected Framework.

Amazon Connect AI Customer Engagement

Amazon Connect AI and ML Fundamentals

Foundational overview of AI and machine learning features in Amazon Connect, including Contact Lens, Voice ID, and generative AI assistance. Explains how these capabilities integrate with the contact center to improve customer and agent experience.

Getting Started with Administering Amazon Quick Suite

Administrator orientation to Amazon Quick Suite, the agentic AI-powered workspace. Covers tenant setup, user and group management, data source connections, governance settings, and monitoring usage and costs.