AI | GenAI | AWS | Amazon Q Business | Create ChatGPT | 2026

Explore artificial intelligence, its data-driven learning via machine learning, natural language processing, and computer vision, and its applications in healthcare, finance, customer service, plus deep learning trends and job impacts.

Understand how IAM organization centralizes management of multiple AWS accounts from a single place with consolidated billing, centralized policy management, and service control policies for cross-account access.

This lecture explains creating an aws organization, inviting or adding accounts, building organizational units, and applying service control and tag policies for consolidated governance.

Explore Amazon S3, a scalable cloud storage service in aws. Store data anywhere on the web with buckets and objects, backed by durability, encryption, and replication options.

Explore IAM Identity Center, a cloud service that centralizes user and group management across AWS accounts and applications, assigns permission sets, and enables single sign-on with secure SSL integration.

Enable the IAM Identity Center to centrally manage users, groups, and permissions across AWS accounts from a dashboard, configure identity sources, and assign permission sets with MFA/OTP for secure access.

Enable the IAM Identity Center in a single AWS account and manage AWS organizations from Identity Center, including deletion by ID and auto-creation in North Virginia (Test Network).

Create and manage users in the IAM Identity Center to grant access to AWS resources, including usernames, emails, passwords, and optional group assignments.

Enable users in the IAM Identity Center by guiding invite acceptance within seven days. Set up a one-time password and MFA with built-in macOS authenticator or apps, then assign permissions.

Assign permissions to users in the AWS identity center by creating predefined or custom permission sets. Provide administrator or read-only access, assign to accounts, and set session duration.

Explore how amazon q, an ai generative assistant from aws, helps employees find information, solve tasks, and generate or debug code using data and services like quicksight and amazon connect.

Take a practical UI tour of the Amazon Cube to understand its centralized admin hub, enable the Identity Center, and manage subscriptions, users, groups, and applications in one place.

Explore Amazon Q business, an enterprise AI assistant that answers questions, summarizes data, and generates content from your company documents, while securely indexing sources.

Discover how Amazon Business Queue enhances industry workflows by building trust, automating tasks, protecting brands, and boosting time to value with source-attributed answers, native connectors, and plugins.

Understand the Amazon Q workflow from data ingestion and identity management to query filtering, guarded by permissions, and response generation using LLM models, plugins, or rag.

Learn how IAM roles in Amazon queue handle authorization and authentication, contrast service roles with service link roles, and apply least privilege to EC2 accessing S3.

Explore how the Amazon Cube business unit enables internal applications, from getting started and trying a quick app to creating a new service with service linked roles, encryption, and plugins.

Compare starter and enterprise index plans on amazon, noting availability zones, document capacity 100k vs 1 million, hours, encryption, and suitability for proof of concept or production workloads.

Implement user provisioning in Q Business by importing users from IAM Identity Center, then assign subscriptions to the new users for centralized management.

Explore Amazon Q business subscriptions, comparing Lite and Pro plans, including Q&A, permission awareness, single sign-on, PDF uploads, custom plugins, and QuickSight insights.

Explore how to manage user subscriptions in the AWS console by assigning light or pro plans, with pro enabling features like a generative assistant and content generation, plus pricing differences.

Explore how a retriever indexes and crawls documents, fetches data in real time via Amazon Kendra or native queue, and provides context to an LLM for succinct responses.

Enable retriever settings in the Amazon queue to add data sources, choose native or existing retriever, and select starter or enterprise provisioning for cost and availability.

Test a queue application without a data source by signing in with MFA using two users, and observe that without data the app cannot produce relevant information.

Explore retrieval augmented generation, a two-phase approach that retrieves relevant data from a knowledge base and generates user-ready text, powering accurate, context-aware responses for customer support and healthcare.

Explore how a large language model understands, generates, and manipulates language—handling synonyms, translation, summarization, and content generation across diverse inputs.

Crawl data from web pages using spiders and schedulers. Index collected information with keywords and metadata to enable fast retrieval.

Discover how data sources power Amazon Q retriever, including connectors for S3, Confluence, GitHub, PDFs, and how to configure, index, and schedule data for search.

Upload data source files in the Amazon Q business app, let them index and process, then use the indexed data to generate outputs.

Configure S3 as a data source by creating a bucket, uploading files, and wiring in IAM roles, then use full or on-demand sync to index and access the data.

Learn how Amazon Q business answers questions using customer data or the built-in LM model, with a toggle between data sources and direct responses plus fallback when data is missing.

Learn how fallback answers combine enterprise data and a built-in LM to respond when topics lack sources, with admin controls guiding when to use each.

Explore guardrails for Amazon queue apps that block words and topics to protect confidential information, control file uploads, and choose responses from enterprise data or built-in AI.

Configure global and per-word blocks using admin controls and guardrails in the Amazon Q business app; test with fruits and vegetables and see blocked responses when keywords are restricted.

Create and manage topics in Amazon queue to enforce guardrails, block or restrict content, and apply topic-specific rules for user groups and enterprise data.

Empower users to choose answers from data sources or the LLM, enabling direct LLM queries via admin controls, and illustrate switching between sources and LLM responses.

Customize the web experience in the app by editing welcome messages, sample prompts, and inputs, saving changes, and reviewing the refreshed interface with fallback handling.

Learn how Amazon Q plugins extend the platform with tools like Jira, Salesforce, ServiceNow, and Zendesk, plus custom plugins via APIs to read, write, and create issues from chat.

Explore Jira, a centralized project management tool for issue tracking and agile workflows, that uses epics, stories, tasks, and bugs on scrum or kanban boards.

Add a Jira plugin to Amazon cube and configure it with Jira URL and API token via secret manager. Create issues and epics directly on your Kanban or Jira board.

Create Jira issues from the Amazon queue using the Jira plugin in the AWS console to support sprint or kanban workflows by selecting board, project, priority, and reporter.

Discover how apps in Q Business turn chat interactions into reusable AI-powered apps for automating scheduled tasks across teams, from HR to marketing, with one-click creation.

Create apps from repetitive tasks using the amazon queue and aws to generate a structured learning plan with exercises, then publish and access it in the library.

Compare pro and lite subscriptions for Amazon Q Business to reveal differences in features, such as file uploads, plugins, and content generation, versus basic Q&A.

Discover Amazon Kendra, a machine-learning intelligent search service delivering accurate, unified search across 40+ data sources with natural language processing and continuous learning integrated with Amazon Q Cube.

Learn to set up AWS Kendra to crawl and index an S3 data source and integrate it with the Amazon queue, including creating an index and data sources.

Explore hands-on use of Kendra as the driver for Amazon Q Business, building a centralized retriever-based application and deploying a test index for streamlined data access.

Explore Confluence, a centralized collaboration and knowledge management platform for creating, sharing, and organizing pages and spaces with real-time collaboration, multimedia content, and Jira or Trello integrations.

Connect Confluence as a Kendra data source, configure Confluence Cloud with API token or ACL, then sync and crawl to index pages for the retriever.

Connect public websites to Amazon Kendra using the web crawler connector, configure sources, sitemaps, and authentication options, and run full-sync indexing to surface summarized results quickly.

Understand how attributes enable document enrichment and tuning in the Amazon Business app, using indexing by name, title, creation date, and authors, with Lambda-based OCR processing and weighted relevance.

Learn to use attributes for document enrichment and relevance tuning in the Amazon queue business, configuring data sources such as the S3 bucket and uploaded files to refine indexing.