This module provides an introduction to AWS Identity and Access Management (IAM) and Amazon S3, covering key concepts like user and role management, policy attachment, and secure cloud storage. Learners will gain hands-on experience configuring IAM Organizations and working with S3 for scalable storage solutions.

This module provides an in-depth look at AWS IAM Identity Center, covering its role in simplifying identity management, the process of enabling it through different options, and how to add and manage users and permissions. Learners will gain practical knowledge on configuring and securing access to AWS resources.

This module provides an in-depth overview of Amazon Q Business, covering its functionality, user interface, industry applications, and security features. Learners will gain a clear understanding of how it supports enterprise AI assistance and organizational knowledge access. The module also includes a hands-on exploration of its configuration and workflow.

This module explores key components of Amazon Q Business, including index plans, user management, subscriptions, and retriever settings. Learners will gain hands-on experience in configuring and testing Q Business applications. The focus is on understanding and implementing core features for effective enterprise data management.

This module covers the integration and management of data sources in Amazon Q, including uploading files, using Amazon S3, and configuring fallback answers. Learners will also explore methods to restrict information, control responses, and dynamically manage data sources. By the end, students will be able to customize and enhance their Amazon Q applications effectively.

This module introduces foundational concepts in AI systems, including Retrieval Augmented Generation, Large Language Models, and data crawling and indexing. Learners will gain an understanding of how these technologies support and enhance AI capabilities. The content provides a clear overview of the technical components involved in modern AI operations.

This module explores how to set up and integrate Amazon Kendra with Amazon Q Business, covering data source connections, enrichment techniques, and search optimization. Learners will gain hands-on experience with enterprise search capabilities and knowledge management tools.

This module covers how to extend the functionality of Amazon Q Business using plugins and apps. Learners will explore Jira integration, app development, and subscription tier comparisons to enhance productivity and system customization.