Hands-On Labs

AWS Certified AI Practitioner (AIF-C01)

Build real cloud skills with guided labs on AWS and Google Cloud. Practice in live environments with instant access to real cloud resources. No cloud account required.

11
Available Labs
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Fundamentals of AI and ML

2 labs available

🌱 Beginner
155m

Understanding Foundational AI Concepts with Amazon Bedrock

In this lab, you will explore foundational AI concepts using Amazon Bedrock, a service that enables the easy integration of AI capabilities into your applications. By the end of this lab, you will understand the basics of AI and learn how foundation models are used in practice to derive insights from data.

5 tasks
Understanding foundational AI concepts and terminologiesConfiguring and using Amazon Bedrock for AI tasksIntegrating datasets with AI models
🌱 Beginner
140m

Getting Started with Amazon Bedrock for AI Workflows

In this beginner-level lab, you will explore Amazon Bedrock, a foundational service for building AI workflows. You will set up a basic environment using Amazon Bedrock that can support AI-powered applications, focusing on knowledge bases and integrating guardrails to ensure model safety.

5 tasks
Setting up Amazon Bedrock for AI workflowsIntegrating knowledge bases and configuring guardrails

Fundamentals of Generative AI

2 labs available

🌱 Beginner
110m

Introduction to Amazon Bedrock for Generative AI

In this hands-on lab, you will explore Amazon Bedrock, a foundational service for building generative AI applications. You will learn how to access pre-built models, configure basic lifecycle concepts, and understand the benefits of using Amazon Bedrock for AI solutions.

5 tasks
Understanding foundational generative AI conceptsIdentifying potential use cases for generative AI modelsDescribing AWS services and features for generative AI applications
🌱 Beginner
90m

Introduction to Amazon Bedrock for Generative AI

In this lab, you will explore Amazon Bedrock, a foundational service for creating and deploying generative AI models. You'll learn how to navigate Bedrock’s interface, understand its key features, and set up a base project using foundation models.

5 tasks
Exploring foundational concepts of generative AI using Amazon BedrockEvaluating business applicability of AI modelsUnderstanding AWS services supporting generative AI

Applications of Foundation Models

4 labs available

🌱 Beginner
130m

Foundation Models and Retrieval Augmented Generation with Amazon Kendra and Bedrock

This lab demonstrates the integration of foundation models with enhanced search capabilities using Amazon Kendra and Amazon Bedrock. You will explore Retrieval Augmented Generation to improve response accuracy and relevancy through advanced search techniques.

5 tasks
Applying RAG concepts to enhance AI search capabilitiesConfiguring and securing AI models using AWS servicesDocumenting AI strategy and performance evaluation
🌱 Beginner
60m

Explore Amazon Bedrock for Foundation Models

In this lab, you will explore Amazon Bedrock, a service that provides a flexible interface to access foundation models for various generative AI tasks. You'll learn how to select and deploy a pre-trained model for a specific use case, emphasizing cost-effective decision making and proper prompt engineering techniques.

5 tasks
Selecting pre-trained models based on business needsUsing Amazon Bedrock for model deploymentApplying prompt engineering techniques
🌱 Beginner
150m

Improving AI Model Fine-Tuning with Amazon SageMaker JumpStart

Use Amazon SageMaker JumpStart to explore fine-tuning pre-trained models. This lab will guide you through selecting, tuning, and evaluating AI models to achieve optimal performance.

5 tasks
Utilizing pre-trained models in AI applicationsApplying fine-tuning techniques to enhance model performanceEvaluating and reporting on AI model performance enhancements
🌱 Beginner
120m

Explore Amazon Bedrock for Enterprise AI

This lab introduces you to Amazon Bedrock, a key service for building generative AI applications. You'll explore how to select and configure foundation models tailored for specific business requirements.

5 tasks
Choosing appropriate foundation models for AI applicationsApplying prompt engineering techniques to improve model responsesEvaluating AI model performance using industry metrics+2 more

Guidelines for Responsible AI

1 lab available

🌱 Beginner
60m

Creating Responsible AI Models with Amazon SageMaker

In this lab, you will learn how to create AI models responsibly using Amazon SageMaker. You will explore how to utilize Amazon SageMaker Clarify to detect bias and ensure your models are transparent and explainable.

5 tasks
Understanding SageMaker for responsible AIUsing SageMaker Clarify for bias detectionApplying model explainability techniques

Security, Compliance, and Governance for AI Solutions

2 labs available

🌱 Beginner
100m

Getting Started with Amazon Bedrock and IAM for Secure AI Systems

Learn to secure your AI systems by integrating Amazon Bedrock with AWS IAM. This lab introduces you to foundational security practices using Amazon Bedrock, teaching you how to create IAM roles for access control and security within AI solutions.

5 tasks
Configuring IAM roles for secure AI system managementApplying encryption policies in AWS for data protectionImplementing governance protocols for AI resource management+2 more
🌱 Beginner
60m

Getting Started with Amazon SageMaker JumpStart

In this lab, you will explore Amazon SageMaker JumpStart, a service that provides quick access to pre-built models and solutions. You will learn how to deploy a pre-built model and make inferences, which simplifies the use of machine learning in your applications.

5 tasks
Deploying pre-built models with Amazon SageMaker JumpStartRunning inferences in Amazon SageMakerUnderstanding governance features in Amazon SageMaker