Python
181 courses4 categories
Part of LearnProgramming
Python is a high-level, dynamically typed language that has become the default choice for data work, machine learning, automation, scripting, and a large share of backend services. The topic covers the language itself (3.12 / 3.13 era), the standard library, the ecosystem of frameworks and packages, and the surrounding tooling for testing, packaging, and deployment.
The 2026 reality is that Python sits in two very different worlds. On the web side, Django and FastAPI handle most new backends, with uv and ruff replacing the older pip / pip-tools / black / flake8 stack across many teams. On the data and AI side, the language is unavoidable: pandas and polars for analysis, NumPy and PyTorch for numerics and ML, Jupyter for exploration, and nearly every LLM SDK shipping a Python client first.
What you'll find under this topic
- Language fundamentals: type hints, dataclasses, async/await, pattern matching
- Web frameworks: Django, FastAPI, Flask, Starlette
- Data processing and analysis: pandas, polars, NumPy, DuckDB, pyarrow
- Math and statistics foundations for ML and analytics
- Automation and scripting: requests, Playwright, Selenium, system tasks
- Testing and tooling: pytest, ruff, mypy, uv, Poetry
- Deployment: Gunicorn / Uvicorn, Docker, serverless and ASGI workers
Python skills hire across an unusually wide range of employers: AI labs and ML-heavy startups, fintech and banks running risk models, scientific and research organizations, every SaaS company with an internal analytics function, and the long tail of teams using Django or FastAPI for their main product. Roles include backend engineer, data engineer, ML engineer, analytics engineer, and the increasingly common AI / applied-ML engineer.
Categories(4)
Data processing and analysis covers the day-to-day work of turning raw operational data into something a person or…
Django is a high-level web framework designed in Python and developed by the Django Software Foundation to promote…
Math & Statistics underpin many aspects of software engineering and data science, providing the foundational tools…
Python is a high-level, general-purpose programming language designed around code readability and a deliberately small…
Courses(181)
Showing 1–30 of 181 courses
Updated 1mo agoThe Apache Flink course helps master stream data processing, deploy and optimize real-time pipelines for professional projects.2h 12m
Updated 2mo agoExplore creating AI agents in Python without complex frameworks. Maintain full control over system logic and security, and work directly with AI APIs.2h 33m5/5
Updated 2mo agoLearn to create AI applications using TypeScript and Python, with a focus on practice and using AI tools. Gain skills for development.1h 59m
Updated 4mo agoStart learning Python from scratch: set up the environment, learn the basics, and gain confident programming skills for your own projects.2h 40m
Updated 4mo agoStudy the creation of voice AI agents using AWS and Python. Develop an assistant with real functionalities and a deep understanding of the architecture.3h 1m5/5
Updated 4mo agoMaster the creation of AI applications for investments using Python and LangChain. Practice developing a fintech application and understanding financial metrics7h 36m5/5
FreeUpdated 4mo agoLearn core regression models and use them in Python. You study linear, logistic, log, and Cox models with clear steps and real data.6h 20m
Updated 4mo agoYou learn core inferential stats like intervals, tests, ANOVA, and run them in Python. The course shows how to read messy data and make clear data decisions.9h 25m
Updated 7mo agoLearn to build streaming pipelines with Apache Kafka and Flink, create data lakes on AWS, run ML workflows on Spark, and integrate LLM models.16h 46m
Updated 7mo agoStudy Apache Spark and PySpark for big data processing. Practical assignments will help you acquire key skills of a data engineer.2h 20m
Updated 8mo agoThis is Part 1 of a series of courses intended to dive into the inner mechanics and more complicated aspects of Python 3. This is not a beginner course - if you45h 50m5/5
Updated 9mo agoThis course is an in-depth look at Python dictionaries. Dictionaries are ubiquitous in Python. Classes are essentially dictionaries, modules are dictionaries, n21h 58m5/5
Updated 9mo agoLearn how to use agent AI to create and improve Python applications. Discover the difference from chatbots and customize AI for your tasks.2h 38m5/5
Updated 10mo agoLearn Python from scratch or enhance your programming skills. The course is designed for beginners and professionals, with no programming experience required.
UpdatedLearn analytics engineering hands-on: build a Snowflake warehouse, load data with Fivetran, transform it with DBT, and visualize it.12h 46m
Updated 10mo agoLearn Python from the ground up and use it to build your own AI tools. You start with the basics and grow the skills you need to work with LLMs in real.1h 41m5/5
UpdatedBuild a real semantic search pipeline for logs: FastAPI, embeddings stored in qdrant, a Streamlit UI, and a DuckDB comparison.53m
UpdatedLearn Apache Iceberg hands-on: schema evolution, time travel, and a real local Lakehouse lab with Docker, Spark, and MinIO.33m
Updated 11mo agoThe Hidden Foundation of GenAI gives you a clear start in embeddings. You learn what sits under LLMs, vector search, and semantic tools.20m5/5
UpdatedMove past Python basics into composability, interfaces, and design: writing systems that stay maintainable as they grow.34h 56m5/5
UpdatedLearn Apache Airflow from architecture to advanced orchestration: retries, failure handling, sensors, and Spark integration.2h 21m
FreeUpdatedFree course on scaling machine learning with Spark ML: regression, classification, feature engineering, and hyperparameter tuning.2h 7m
UpdatedBuild a real Azure ETL pipeline with Terraform: Data Factory, Synapse Analytics, Power BI, and a Medallion Lakehouse architecture.4h 20m
Updated 1y agoIn this practical course, you will learn how to build a complete data pipeline on the AWS platform - from obtaining data from the Twitter API to analysis, stora1h 33m5/5
Updated 1y agoEnhance your skills in managing time series data with this comprehensive course.2h 11m5/5
UpdatedSimulate 100,000 users and a million check-ins, then trace movement patterns using Elasticsearch, Kibana, and a Streamlit map UI.1h 37m
Updated 1y agoBig Data is not just a buzzword, but a real phenomenon. Every day, companies around the world collect and process vast amounts of data at high speeds.7h 3m
UpdatedBuild a Dockerized ETL pipeline on AWS: pull live weather data into TDengine and visualize it with Grafana, step by step.29m
UpdatedBuild a real-time invoice streaming pipeline with Kafka, Spark, and MongoDB, visualized through a live Streamlit dashboard.2h 46m
Updated 1y agoThis course is the perfect start for those who want to learn cloud technologies and start working with Amazon Web Services (AWS), one of the most popular..4h 46m5/5
Related topics
Frequently asked questions
- Is Python a good first programming language?
- Yes — Python's syntax is approachable enough for beginners while being one of the most in-demand languages in 2026 for web backends, data science, ML, AI, automation, and scientific computing. The standard library is broad, the ecosystem is mature, and almost every learning resource on earth ships a Python option. Hard to beat as a first language.
- How long does it take to learn Python?
- Most learners reach hireable proficiency in 4–8 months of consistent practice. Foundational fluency comes after roughly 80–120 hours; specialized tracks (data engineering, ML, web with Django or FastAPI) each add another 100+ hours. The language itself is small; what takes time is the ecosystem and idioms specific to your target domain.
- What jobs use Python?
- Backend engineer (Django, FastAPI), data engineer, ML engineer, data analyst, applied AI engineer, automation and QA engineer, scientific computing, security tooling, and a vast amount of internal company tooling. Most AI labs are Python-first, and most fintech and biotech teams have meaningful Python footprints. The breadth is rare among programming languages.
- Should I learn Python or JavaScript first?
- Python if you target data, ML, AI, or backend Linux work; JavaScript if you target web frontends or full-stack JS roles. Both are top-tier choices in 2026 and many strong engineers know both well. The honest answer is to pick the one closest to the kind of job you actually want and learn the other later.
- Free vs paid Python courses — does it matter?
- Free resources (official docs, Real Python, CS50, free university lectures) cover fundamentals very well — many strong Python engineers learned exclusively from free material. Paid courses add structured projects, instructor accountability, and curated paths through advanced topics. Either path works; what matters is shipping projects, not which logo is on the certificate.