Already know basic Python? Build one real thing end to end: a small AI data app that loads a dataset, sends a slice of it to a language model, and turns the response into a written analysis. You will use pandas only as much as the app needs, call an LLM API directly (no agents, no frameworks), wire the pieces into a single script with real error handling, and ship it as a shareable Streamlit app you can run locally. A project-based intermediate course with a free certificate of completion.
You already know a little Python, and you are tired of tutorials that hand you disconnected snippets and never build anything real. This project-based course fixes that by walking you through one complete build: a small AI data app that loads a dataset, sends a compact slice of it to a language model, and shows you a written analysis of what the numbers actually mean. You start in the terminal and finish with a shareable web app.
Across seven focused lessons you load and clean real data with pandas (only as much as the app needs), make your first plain API call to an LLM, design prompts that keep the analysis grounded in real numbers, wire everything into a single script with proper error handling, and wrap it in a clean Streamlit interface with a file upload and an Analyze button. There are no agents and no heavy frameworks here, just direct API calls, so every moving part stays visible and debuggable.
This is an intermediate course for students and self-taught coders who can already read a for loop and a function and now want to apply Python to AI by shipping something usable. It sits between an absolute-beginner Python tour and advanced agent engineering: a hands-on capstone you can put on your resume or GitHub. The pandas and scripting lessons run in interactive Python playgrounds right in the page, so you can practice without installing anything.
The course is 100% free, with no signup wall, and finishing it earns you a free certificate of completion for your LinkedIn and resume.
3 modules • 7 lessons
Finish every lesson and pass the final exam to earn this free, shareable certificate.
Verify
June 15, 2026
This certifies that
has successfully completed the course
Sample preview. Your name appears on the certificate when you complete the course. Learn more
You will build a complete AI data app from scratch: a Python script that loads a CSV, sends a slice of the data to a language model API, and displays a written analysis. The finished project runs locally as a Streamlit app you can share with others.
Yes, the course is completely free. Completing all lessons and passing the final exam earns you a certificate of completion you can add to your LinkedIn profile or resume.
You should already be comfortable with basic Python, such as variables, functions, and loops. The course is designed for intermediate learners who want to move from Python fundamentals to building a real project that calls an AI API.
The course uses pandas for loading and slicing data, a direct LLM API call (no agent frameworks), and Streamlit to package the finished script into a shareable app. You call the AI model yourself, so you see exactly what is happening at each step.
Starting with a direct API call and plain Python gives you a clear mental model of how AI integrations actually work before you add layers of abstraction. Once you understand the core loop of loading data, prompting a model, and handling the response, adding frameworks later becomes much easier.
Level up from Python basics to writing powerful, real-world Python for data, AI, and automation. Master classes and dataclasses, comprehensions and generators, decorators, context managers, robust error handling, type hints, packaging, working with files and APIs, and a practical intro to async. Hands-on examples and a free certificate of completion.
Build a working AI agent from scratch in Python. Learn the think-act-observe loop, call an LLM, give your agent a tool it can use, and handle a failed tool call. Framework-agnostic and beginner-friendly.
Learn Python from zero with a focus on AI and data science. Master the language essentials, then use ChatGPT, Claude, and Gemini as coding tutors while you build real projects with NumPy, pandas, matplotlib, and scikit-learn. Perfect for university students and early-career learners. No prior coding required, and you earn a free certificate to add to your LinkedIn and resume.
Build autonomous AI agents with Python using LangChain and LangGraph. Learn tool calling, stateful workflows, RAG-powered agents, multi-agent systems, and production deployment. From the ReACT pattern to a full customer support agent capstone.
Build a private, offline knowledge base over your own notes and PDFs using a local AI model. A hands-on beginner micro course: run a model with Ollama, turn documents into embeddings, store them in a local Chroma database, and ask questions answered from your own files. No cloud APIs, no fees, your data stays on your machine. Want to deploy it as a web app instead? See the Full-Stack RAG course (/courses/fullstack-rag-nextjs-supabase-gemini).
Learn to build multi-agent AI systems with CrewAI in about 45 minutes. Understand the crew/agent/task model, define specialized agents, create tasks, and build a real-world market research crew with analyst, researcher, and writer agents.
