Data Science

Open Source Tools for Data Science introduces students to the open-source ecosystem that powers modern data science and AI workflows. The course covers collaborative version control with Git and GitHub, Linux-based development and containerization using WSL2 and Podman, infrastructure practices for reproducible AI services (Docker Compose, environment security, DevContainers), open-source LLM and vector database frameworks (Ollama, ChromaDB, LangChain, LlamaIndex), and deployment of AI applications using FastAPI, Gradio, and CI/CD pipelines. Through hands-on classroom sessions on their own laptops, students build practical, in-demand skills while completing a capstone project that ties together an end-to-end open-source data science workflow — from version-controlled code to a deployed, containerized application.