Course Crafter

🎯 Inspiration

Learning online can be overwhelming. Resources are scattered, unstructured, and often too generic or behind paywalls. I wanted to create a tool that could understand a learner’s unique constraints—like time, budget, and content preference—and instantly generate a customized, actionable roadmap. That’s how CourseCrafter was born.

⚙️ What it does

CourseCrafter generates personalized learning plans using an AI language model.
Users input:

a topic,
how much time they have,
their budget,
and preferred content type (e.g., video, text, etc.)

The app then returns a detailed, well-structured course plan with real resource links and a study schedule. The user can also download the plan as a .txt file.

🧱 How I built it

Frontend: I used Gradio to build a clean and interactive UI.
Backend: I deployed an AWS Lambda function to parse user input and forward it to the LLM.
AI Engine: I used Modal to host a FastAPI server running a large language model (Meta LLaMA 3 or Mistral).
Deployment: The Gradio app runs on Render or Hugging Face Spaces, while the backend and model are served through AWS Lambda and Modal.

🧗 Challenges I ran into

🌀 Debugging nested JSON payloads in AWS Lambda
❌ Handling CORS errors and HTTP 500s from API Gateway
💾 Managing Git LFS and "no space left on device" errors in Gitpod
🔧 Learning the new Modal SDK structure and deploying GPU-backed models
🧪 Testing and validating the end-to-end data flow between Gradio, Lambda, and the LLM

🏆 Accomplishments that I'm proud of

Successfully built and deployed a full-stack AI-powered application end-to-end
Integrated multiple services (Gradio, AWS, Modal) seamlessly
Learned how to deploy and optimize inference for large language models
Created a tool that can actually help learners save time and get started quickly