Build an AI Study Buddy on AWS — Day 2: Serverless GenAI Backend

About this event

⚡ Build an AI Study Buddy on AWS — Day 2 The prototype is ready. Now it's time to build the real backend. In Day 2 of the workshop, we move from a no-code prototype to a serverless generative AI backend. You will build an AWS Lambda function that takes student notes, sends them to Amazon Bedrock, generates an AI summary and five quiz questions, and saves the results to Amazon S3. You will also use Amazon Q Developer to generate and understand code and Amazon CloudWatch to debug the application. 🎯 What you'll learn • Foundation models, tokens and cost • Using the Amazon Bedrock playground • Serverless computing concepts • AWS Lambda fundamentals • Lambda handlers, events and responses • Using Amazon Q Developer to generate and understand code • Calling Amazon Bedrock using the Converse API from Python • IAM execution roles and permissions • Debugging Lambda using CloudWatch Logs • Working with Amazon S3 from Lambda 🛠 AWS Services Amazon Bedrock · AWS Lambda · Amazon Q Developer · Amazon CloudWatch · Amazon S3 🏗️ What you'll build By the end of Day 2, you will have a working backend where: Student Notes → AWS Lambda → Amazon Bedrock → AI Summary + Quiz → Amazon S3 You will also have logs available through CloudWatch for debugging. 🎓 Day 2 Deliverable A working Lambda function that: ✅ Accepts notes ✅ Sends them to Amazon Bedrock ✅ Generates an AI summary ✅ Generates 5 quiz questions ✅ Saves the output to S3 ✅ Produces logs in CloudWatch 👨‍💻 Who should attend? This workshop is beginner-friendly, but basic programming knowledge will be useful for understanding the Lambda and Python portions. Day 1 participation is recommended, since Day 2 builds directly on the AWS setup and S3 resources created previously. 💻 What you need • Laptop • Stable internet connection • AWS account • Completed Day 1 setup • Basic programming knowledge is helpful 🔗 Workshop Journey Day 1 → Foundations + No-Code GenAI Day 2 → Serverless GenAI Backend ← You are here Day 3 → API + Frontend + Deployment