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.
4 módulos • 11 aulas

Master data structures and algorithms with hands-on Python practice. Run real code in your browser: Big-O analysis, stacks, queues, linked lists, hash tables, recursion, searching, sorting, trees, graphs, and the interview patterns that tie them together.

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.

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.

Master web scraping techniques using Python. Learn to extract data from websites using BeautifulSoup and Selenium, handle pagination, deal with anti-scraping measures, and build production-ready data pipelines while following ethical practices.

Master the fundamentals of SQL from scratch. Learn to query, manipulate, and design databases using PostgreSQL. Build real-world database systems through hands-on exercises and a capstone project. No prior database experience required.

Learn to analyze financial data using Python. Master NumPy, Pandas, data visualization, portfolio analytics, technical analysis, financial modeling, and statistical analysis. Build real-world projects including an automated investment research system.