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Generative AI Essentials on AWS is a comprehensive one-day, instructor-led training course designed for professionals with limited prior knowledge of generative AI. The course covers foundational concepts in responsible AI, provides practical experience with AWS generative AI services ( Amazon Bedrock, Amazon Nova 2, Amazon Bedrock Knowledge Bases, and Amazon Bedrock AgentCore). Participants gain hands-on implementation experience with responsible AI principles through Amazon Bedrock Guardrails. Responsible AI serves as a foundational theme throughout all modules, connecting ethical principles to technical implementation. Participants progress from understanding AI fundamentals through implementing solutions, exploring agentic AI capabilities, understanding security and governance considerations, and describing project planning components. Approximately 40% of course time is dedicated to hands-on labs and demonstrations.

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What You'll Learn

  • Explain responsible AI foundations
  • Describe multimodal AI capabilities
  • Implement generative AI solutions using Amazon Bedrock and Amazon Nova 2
  • Explain how retrieval-augmented generation (RAG) enhances AI responses by connecting agents to organizational knowledge sources
  • Describe Amazon Bedrock AgentCore capabilities
  • Apply responsible AI practices using Amazon Bedrock Guardrails
  • Explain security and governance considerations
  • Describe key components of generative AI project planning

Who Should Attend

  • Business analyst
  • IT support
  • Marketing professional
  • Product or project manager
  • Line-of-Business or IT Managers
  • Sales professionals

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Prerequisites

No prior knowledge or preparation is needed

Learning Journey

Coming Soon...

Module 0: Course Introduction

  • Course structure/schedule
  • Five-phase learning journey
  • Responsible AI foundational theme

Module 1: Responsible AI Foundations

  • AI evolution: from traditional to generative
  • Eight dimensions of responsible AI
  • AWS commitment to responsible AI

Module 2: Introducing Generative AI

  • Generative AI Foundation
  • Foundation models and embeddings deep dive
  • Amazon Bedrock and Amazon Nova 2 models
  • Comparing models

Module 3: Multi-Modal AI and use cases

  • Multimodal AI capabilities
  • Industry applications and use cases
  • Use case evaluation framework

Module 4: Essentials of prompt engineering

  • Prompt engineering fundamentals
  • Prompting strategies
  • Prompt security and attach vectors
  • Lab 1 - Optimizing Slogan Generation with Amazon Bedrock

Module 5: Implementing responsible AI with Amazon Bedrock Guardrails

  • Amazon Bedrock guardrails overview and configuration
  • Lab 2 - Implementing Responsible AI Principles with Amazon Bedrock Guardrails

Module 6: Introduction to Amazon Agents

  • Agentic AI concepts
  • Amazon Bedrock capabilities
  • Amazon Bedrock AgentCore overview
  • RAG and Knowledge Bases

Module 7: Introduction to Security, Governance, and Compliance

  • From security principles to organizational accountability
  • Governance frameworks
  • Compliance requirements

Module 8: Implementing generative AI projects

  • Project planning fundamentals
  • Lab 3: Building an HR Assistant with Amazon Bedrock

Module 9: Summary

  • Learning journey recap
  • Next steps

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Frequently Asked Questions (FAQs)

  • Why get AWS certified?

    AWS certifications validate your expertise in cloud computing and your proficiency in using AWS services.

    These certifications are globally recognized and highly sought after by employers, as they demonstrate your ability to design, deploy, and manage scalable and secure cloud solutions on the AWS platform.

    AWS-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

  • What to expect for the examination?

    AWS offers a variety of certification exams at different levels (Foundational, Associate, Professional, and Specialty) covering various domains and services.

    The exams typically consist of multiple-choice and multiple-response questions, and some may include scenario-based questions that assess your ability to apply your knowledge in real-world situations.

    Note: Certification requirements and policies may be updated by AWS from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is AWS certification valid for?

    AWS certifications are valid for three years from the date of passing the exam.

    To maintain your certification, you will need to recertify by passing the latest version of the exam or completing the AWS Cloud Quest game-based training (if option is applicable).

    Note: Certification requirements and policies may be updated by AWS from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 24 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

Keep Exploring

Course Curriculum

Course Curriculum

Training Schedule

Training Schedule

Exam & Certification

Exam & Certification

FAQs

Frequently Asked Questions

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