Online Course

Introduction to Amazon Bedrock

This project-based course provides developers with a practical introduction to Amazon Bedrock, AWS’s fully managed service for building and scaling generative AI applications without managing infrastructure or training models. Through a mix of hands-on labs, guided exercises, and mini-projects, you’ll gain the skills needed to securely invoke, integrate, and deploy foundation models into real-world applications.

The course is organized into six chapters, each building toward a final project:

• Chapter 1: Introduction to Generative AI 
  Understand what generative AI is, how Bedrock simplifies model access, and the benefits of using it over traditional ML workflows.

• Chapter 2: Deep Dive into Foundation Models in Bedrock
  Explore the Bedrock console, compare models from providers like Anthropic, Cohere, Meta, Mistral, Stability AI, and Amazon, and learn how inference parameters (temperature, max tokens, stop sequences) impact results.

• Chapter 3: Programmatic Access via AWS CLI 
  Install and configure the AWS SDK, set up IAM best practices, and write Python scripts to invoke Bedrock models. Learn both synchronous and streaming API calls.

• Chapter 4: Building Real Applications with Bedrock
  Apply Bedrock in a serverless architecture using AWS Lambda and API Gateway. Build and test REST APIs that leverage Bedrock for text generation in a production-ready environment.

• Chapter 5: Managing Costs, Best Practices, and Advanced Topics
  Learn about AWS Bedrock pricing, apply best practices to reduce costs, and configure AWS Budgets and alerts to monitor usage effectively. Brief Introduction into advanced use cases, such as fine-tuning models, applying prompt engineering strategies, and integrating Bedrock into larger enterprise workflows.

Throughout the course, you’ll complete hands-on exercises and mini-projects that reinforce concepts step by step. By the end, you’ll have built and deployed a serverless application powered by Amazon Bedrock.