Learn one of the most popular programming languages in the world and dive into the world of software engineering and data science with our free materials or bootcamp selection that fits your needs.
We offer many resources to test your skills and practice what you learned, working with our partners from around the world, and using real-world examples that you can apply in your career.
After completing your learning and practice, you can earn Python Foundation Certifications to validate your skills and gain international recognition for your knowledge.
Internationally Recognized Certifications
The Python Foundation offers internationally recognized US-based Python Certificates in partnership with the International Standards of Python Development
Yellow belt
Beginner: Able to read and write basic python
Requirements: Complete all Yellow Belt Courses and pass the exam.
black belt
Expert: Able to develop AI applications and advanced data pipelines
Requirements: Complete all Data Science Black Belt courses and pass the exam.
Yellow belt
Beginner: Able to read and write basic python
Requirements: Complete all Yellow Belt courses and materials, and pass the exam.
Green belt
Intermediate: Choose a Path (Software Engineer, Data Science) and deepen your knowledge
Requirements: Complete all Data Science Green Belt courses and pass the exam.
blue belt
Advanced: Mastery of complex programming concepts in your Path
Requirements: Complete all Data Science Blue Belt courses and pass the exam.
black belt
Expert: Recognition in your field, 5+ years of relevant experience, mastery of AI
Requirements: Complete all Data Science Black Belt courses and pass the exam.
Events
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News Stand
The first beta of Python 3.13 is now available for testing. Highlights include the new “static comprehensions” optimization (up to 30 % faster in micro‑benchmarks), expanded tomllib features, and preliminary support for Apple silicon GPUs via Metal. The final 3.13.0 release is scheduled for early October 2025.
Pandas 3.0 has officially shipped, replacing its internal frame with an Apache Arrow‑backed engine. Users see immediate speed‑ups on large joins and group‑bys, and memory usage drops by roughly 40 % on common analytics workloads. A migration guide and compatibility shim (pandas.compat.v2) are provided for legacy codebases.
To combat supply‑chain attacks, the Python Package Index (PyPI) now requires all project maintainers to enable two‑factor authentication by June 1 ‑ 2025. Accounts without 2FA after that date will be restricted to read‑only until 2FA is activated. PyPI is offering free hardware security keys through the OpenSSF Mobilization Fund for qualifying maintainers.
From Our Partners
Why read: Discover a hands‑on framework for driving growth through disciplined, Python‑powered A/B testing.
In this guide you’ll learn to:
Design statistically sound experiments in Jupyter using scipy.stats
Ship variants instantly via Django/Flask feature‑flags and rollout scripts
The pain: Ad spend north of $50 M can’t be optimized if your CSVs fight your ETL.
The fix: A Python‑first standards blueprint—Parquet, Arrow, dbt, and Pydantic schemas—that keeps pipelines clean from clickstream to dashboard.
Inside:
* Schema stubs you can drop straight into Airflow DAGs
* Code snippets to validate events with pydantic.dataclasses
* A case study showing 40 % faster attribution queries on DuckDB
* Code snippets to validate events with pydantic.dataclasses* A case study showing 40 % faster attribution queries on DuckDB
Reality check: “Hello {name}” isn’t personalization. Real‑time, context‑aware recommendations are.
Solution stack: FastAPI, Faiss vector search, and Redis streams—no proprietary black boxes.
You’ll learn:
* How to embed product catalogs with sentence-transformers
* Sub‑50 ms similarity look‑ups with Faiss + NumPy
* Privacy‑safe feature stores using DuckDB & Parquet
Feedback
To The Python Foundation, I extend my heartfelt thanks. Your commitment to hosting such an inspiring event is commendable. The experience has super‑charged my engineering toolkit and refreshed my problem‑solving mindset. My confidence has soared, and I now feel armed with cutting‑edge Python strategies that will propel me—and my team—to new heights.”
Parissa Burton
Software Engineer | Data & Brand Strategist