ARTIFICIAL INTELLIGENCE · 4 WEEKS · 92 LESSONS

Generative AI and LLMs on AWS

Learn to build and deploy generative AI applications using AWS services, Amazon Bedrock, and modern development tools. Gain hands-on experience with LLMs, prompt engineering, and AI-powered coding assistance through practical projects and real-world scenarios.

Master the implementation of generative AI and large language models (LLMs) on Amazon Web Services through comprehensive hands-on training. This course covers AWS cloud fundamentals for AI, development environments using Rust and Python, serverless solutions with Amazon Bedrock, prompt engineering techniques, and practical applications including CodeWhisperer integration. Students will gain expertise in building AI-powered applications, working with foundation models, implementing knowledge bases and RAG systems, and developing end-to-end AI solutions using AWS services and modern programming languages.

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01 — What learners say

Real feedback from real learners.

“The Rust Fundamentals course was fantastic for formalizing my base Rust knowledge. It was well-paced for both beginner and experienced developers.”

Jeff Mitchell
Full Stack Developer

02 — Why this course

What you'll walk away with.

Master the implementation of generative AI and large language models (LLMs) on Amazon Web Services through comprehensive hands-on training. This course covers AWS cloud fundamentals for AI, development environments using Rust and Python, serverless solutions with Amazon Bedrock, prompt engineering techniques, and practical applications including CodeWhisperer integration. Students will gain expertise in building AI-powered applications, working with foundation models, implementing knowledge bases and RAG systems, and developing end-to-end AI solutions using AWS services and modern programming languages.

01

Understand AWS cloud computing fundamentals and set up AI-focused development environments using Rust and Python

02

Implement generative AI solutions using Amazon Bedrock, foundation models, and knowledge bases with RAG architectures

03

Master prompt engineering techniques and integrate AI coding assistance tools like CodeWhisperer into development workflows

04

Build serverless AI applications and deploy end-to-end solutions using AWS Lambda, Bedrock agents, and modern programming practices

4 weeks, 92 lessons — hands-on labs, quizzes, and a certification.

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03 — Syllabus

4 weeks, 92 lessons total.

Week 1
  • Course introduction
  • Meet your instructor NOAH gift
  • Course structure and discussion Etiquette
  • Key terms
  • Aws cloud adoption framework for AI
  • Cloud service model for AI
Week 2
  • Key terms
  • Prompt engineering Workflows
  • Summarizing text with Claude
  • Prompt engineering
  • Prompt engineering
  • Lesson reflection
Week 3
  • Key terms
  • Key components of amazon Bedrock
  • What is amazon Bedrock
  • Lesson reflection
  • External lab amazon Bedrock prompt engineering challenge
  • Quiz
Week 4
  • Key terms
  • Introduction to cargo lambda
  • Cargo lambda
  • Building RUST add function for AWS lambda
  • Challenge lab Bedrock agents
  • External lab prompt engineering RUST challenge

04 — For teams

Custom training for your company.

We're ready to deliver this and other courses to your team. We accommodate different requirements and are flexible with seat count.

  • +Bulk pricing available
  • +Customizable content
  • +Ready to start on your schedule
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05 — Individual access

Simple, straightforward pricing.

Full platform access — every current and future course — priced so cost isn't what decides whether you learn.

$20/ month

No commitment required. Cancel anytime.

+Every current and future course
+Learn in your own environment, guided end to end
+Self-paced — built around your life
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