Overview

In this course, you will learn about the fundamental concepts, methods, and strategies for using generative AI. You will gain a solid understanding of use cases where generative AI can provide solutions and address business needs. Additionally, you will learn about practical insights into technologies related to generative AI and how you can use those technologies to solve real-world problems. By the end of the course, you will explore project planning and how to discuss implementation of generative AI in your organization.

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Prerequisites

There are no prerequisites for this course.

Target Audience

This course is intended for those with limited prior knowledge of generative AI:

  • Business analysts
  • IT support
  • Marketing professionals
  • Product or project managers
  • Line-of-business or IT managers
  • Sales professionals
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Learning objectives

In this course, you will learn to:

  • Summarize generative AI concepts, methods, and strategies
  • Discuss the appropriate use of generative AI and machine learning and their technologies
  • Describe how to use generative AI responsibly and safely
  • Recognize the types of generative AI solutions with specific use cases
  • Explain implementation and project planning of generative AI to your organization
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Course Outline

Module 1: Introducing Generative AI

  • Generative AI explained
  • Foundation models
  • AWS generative AI services
  • Demo: Generative AI solution

Module 2: Exploring Generative AI Use Cases

  • Identify suitable use cases
  • Generative AI applications and use cases
  • Explore generative AI use case scenarios
  • Use case for class

Module 3: Essentials of Prompt Engineering

  • Introduction to prompt engineering
  • Prompt design best practices
  • Advanced prompting strategies
  • Model settings and parameters
  • Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock

Module 4: Responsible AI Principles and Considerations

  • Introduction to responsible AI
  • Core dimensions of responsible AI
  • Generative AI considerations
  • Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails

Module 5: Security, Governance, and Compliance

  • Security overview
  • Adverse prompts
  • Generative AI security services
  • Governance
  • Compliance

Module 6: Implementing Generative AI Projects

  • Introduction – Generative AI application
  • Define a use case
  • Select a foundational model
  • Improve performance
  • Evaluate results
  • Deploy the application
  • Demo: Amazon Q Business

Module 7: Integrating Generative AI into the Development Lifecycle

  • Introduction
  • Hands-on Lab: Capstone – Creating a Project Plan with Generative AI

Module 8: Course Wrap-up

  • Next steps and additional resources
  • Course summary
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Why choose QA

Dates & Locations

Need to know

Frequently asked questions

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QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.

All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.

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When will I receive my certificate?

Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.

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