Training AWS

Training goals

code: AWS-GAIEA

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.

 

Course 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

 

Intended audience

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

  • Business analysts
  • IT supports
  • Marketing professionals
  • Product or project managers
  • Line-of-business or IT managers
  • Sales professionals

Conspect Show list

  • 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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Additional information

Prerequisites

None
Difficulty level
Duration 1 day
Certificate

The participants will obtain certificates signed by AWS (course completion). This course also helps you prepare for the AWS Certified AI Practitioner (AIF-C01) exam and this way gain the AWS Certified AI Practitioner title – foundational level. AWS certification exams are offered at Pearson Vue test centers worldwide https://home.pearsonvue.com/Clients/AWS.aspx
Trainer

AWS Authorized Instructor (AAI)

Other training AWS | Machine Learning

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Sessions organised at Compendium CE are usually held in our locations in Kraków and Warsaw, but also in venues designated by the client. The group participating in training meets at a specific place and specific time with a coach and actively participates in laboratory sessions.

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You may participate from at any place in the world. It is sufficient to have a computer (or, actually a tablet, or smartphone) connected to the Internet. Compendium CE provides each Distance Learning training participant with adequate software enabling connection to the Data Center. For more information, please visit dlearning.eu site

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