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marcusJunior- Instructor Rating - Reviews - Students - CoursesNo biography available, please complete
🚀 Course Goals
- Install and verify a reproducible Python 3.14 workspace with uv, Git and VS Code on Windows, macOS or Linux. Write clear Python with the right data types, collections, functions, modules and object-oriented design. Read tracebacks, debug from evidence, handle expected failures and add useful logging. Persist data safely in TXT, CSV, JSON and SQLite, with atomic writes, backups, transactions and SQLAlchemy. Automate real work: command-line tools, safe file operations with dry runs, ethical web scraping and API clients.
- Analyze data with NumPy and pandas, validate it, and publish truthful charts and reproducible reports. Build and test a FastAPI REST API, a Django full-stack web application and a bot with a local simulator. Write typed, tested code with mypy, pytest, fixtures, mocks and meaningful coverage. Use generators, decorators, asyncio and profiling to write efficient code and measure it honestly. Package, document and ship your work with pyproject.toml, GitHub Actions CI and Docker, and present a 15-project portfolio.
📘 About This Course
Learn modern Python from zero, build strong programming foundations, automate real work, analyze
data, create APIs and web applications, build a useful bot, test and package professional code, and
finish with 15 portfolio-ready projects.
This is not a list of disconnected syntax features. Every module solves a visible problem and ends
with something that runs: a unit converter and a number game in the first weeks, then an expense
tracker, a contact book with safe persistence, a log analyzer, a library management system, a tested
text toolkit, a safe file organizer, an ethical price monitor, a weather and travel dashboard, a sales
analytics report, an inventory manager on SQL, a FastAPI task manager, a Django freelance job board and
a productivity assistant bot.
Every lesson is a real, uncut session in VS Code and a real terminal on Python 3.14. You watch
each tool being installed from its official source and verified, the code being typed line by line,
and the program being run. Each lesson also contains a controlled failure: a wrong
interpreter, a shared mutable default, a broad except that hides a bug, a join that
multiplies rows, a duplicate write after a retry. You see the symptom, read the evidence, apply the
smallest correction and rerun until the result is right. That is the habit that turns a beginner into
a developer.
About 25 % of the time explains and 75 % demonstrates, codes and debugs. The modern stack
is used throughout: uv with pyproject.toml and uv.lock, Git, Ruff,
mypy, pytest and coverage, HTTPX, Beautiful Soup, NumPy, pandas and Matplotlib, SQLite and SQLAlchemy
2, FastAPI and Pydantic, Django, asyncio, Docker and GitHub Actions. Every lesson ships with its slide
deck and the exact code executed on screen. All data is synthetic and nothing requires a paid
account, a GPU or a paid API.
What You'll Learn
Install and verify a reproducible Python 3.14 workspace with uv, Git and VS Code on Windows, macOS or Linux.
Write clear Python with the right data types, collections, functions, modules and object-oriented design.
Read tracebacks, debug from evidence, handle expected failures and add useful logging.
Persist data safely in TXT, CSV, JSON and SQLite, with atomic writes, backups, transactions and SQLAlchemy.
Automate real work: command-line tools, safe file operations with dry runs, ethical web scraping and API clients.
Analyze data with NumPy and pandas, validate it, and publish truthful charts and reproducible reports.
Build and test a FastAPI REST API, a Django full-stack web application and a bot with a local simulator.
Write typed, tested code with mypy, pytest, fixtures, mocks and meaningful coverage.
Use generators, decorators, asyncio and profiling to write efficient code and measure it honestly.
Package, document and ship your work with pyproject.toml, GitHub Actions CI and Docker, and present a 15-project portfolio.
🛠️ Requirements
- No prior programming, command-line, mathematics, web, database or data-science knowledge is required.
- Basic computer use: files, folders, copy and paste, a browser and browser downloads.
- A computer with a 64-bit 4-core CPU, 8 GB RAM and 35 GB of free disk, running Ubuntu 22.04+, Windows 11 with WSL2 or a recent macOS.
- Permission to install Python, Git, VS Code and the course dependencies; no GPU, paid cloud account or paid API needed.
👤 Who This Course is For
- Complete programming beginners who want a structured path from the first line of code to professional practice.
- Professionals who want to automate repetitive work with reliable scripts.
- Students preparing for data, backend, QA, automation or junior Python developer roles.
- Developers coming from another language who want a modern, structured Python refresh.
- Creators and career changers who want 15 demonstrable projects rather than passive theory.
53618 Students applied
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John Doe
Morbi nec nisi ante. Quisque lacus ligula, iaculis in elit et, interdum semper quam. Fusce in interdum tortor. Ut sollicitudin lectus dolor eget imperdiet libero pulvinar sit amet
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John Doe
Morbi nec nisi ante. Quisque lacus ligula, iaculis in elit et, interdum semper quam. Fusce in interdum tortor. Ut sollicitudin lectus dolor eget imperdiet libero pulvinar sit amet
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John Doe
Morbi nec nisi ante. Quisque lacus ligula, iaculis in elit et, interdum semper quam. Fusce in interdum tortor. Ut sollicitudin lectus dolor eget imperdiet libero pulvinar sit amet
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John Doe
Morbi nec nisi ante. Quisque lacus ligula, iaculis in elit et, interdum semper quam. Fusce in interdum tortor. Ut sollicitudin lectus dolor eget imperdiet libero pulvinar sit amet
Morbi nec nisi ante. Quisque lacus ligula, iaculis in elit et, interdum semper quam. Fusce in interdum tortor. Ut sollicitudin lectus dolor eget imperdiet libero pulvinar sit amet