21 chapters. 4 parts. One project thread that grows with you. Go from zero Python experience to writing clean, professional-grade code — with a real project you build chapter by chapter.
What You'll Learn
Curriculum — 4 Parts, 21 Chapters
Every chapter includes exercises, quizzes, and a chapter extension of the Coffee Shop Simulator project. No time caps — learn at your pace.
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01▾Getting Started with PythonInstallation, your first script, and how Python works
Install Python and VS Code, write and run your first program, and understand how the interpreter executes code. By the end you'll have a working environment and a clear mental model of what Python does under the hood.
~12 hrs InstallationPython interpreterVariablesprint()Data typesComments -
02▾Strings, Numbers, and InputText manipulation, arithmetic, and user interaction
Work with strings in depth — slicing, formatting, f-strings, and common methods. Handle integers, floats, and arithmetic. Capture user input with input() and validate it.
~13 hrs f-stringsString methodsType castingMath operatorsinput() -
03▾Control Flow — Decisions and Loopsif/elif/else, for, while, and program logic
Make your programs smart. Write conditional logic, build loops that repeat until conditions are met, and control program flow with break, continue, and pass. Cover nested loops and common loop patterns.
~13 hrs if/elif/elsefor loopswhile loopsbreak/continuerange()Nested loops -
04▾Functions — Writing Reusable Codedef, parameters, return values, and scope
Functions are the core unit of reusability. Define them, pass arguments (positional, keyword, default), return values, and understand scope. Introduce lambda functions and first-class functions.
~13 hrs defParameters/argumentsReturn values*args/**kwargsScopeLambda -
05▾Data Structures — Lists, Dicts, Tuples, SetsStoring and organizing collections of data
Python's built-in data structures are everything. Learn when to use lists vs. dicts vs. tuples vs. sets. Deep-dive into dictionary operations, list mutations, and set math. Build mental models for performance trade-offs.
~14 hrs ListsDictionariesTuplesSetsIndexing/slicingNested structures
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06▾Object-Oriented ProgrammingClasses, objects, inheritance, and encapsulation
The biggest leap in any Python journey. Learn to model real-world entities as classes, use __init__ and instance methods, implement inheritance chains, and understand dunder methods. Build multiple classes from scratch.
~15 hrs class__init__Inheritancesuper()EncapsulationDunder methods@property -
07▾File I/O and Data PersistenceReading, writing, and working with files and formats
Learn to read and write plain text, CSV, and JSON files. Understand file modes, context managers, and path handling with pathlib. Work with real-world data formats and build programs that remember state between runs.
~13 hrs open()with statementCSV modulejson modulepathlibFile modes -
08▾Error Handling and Exceptionstry/except, custom exceptions, and defensive programming
Programs crash. Good programs don't. Master try/except/else/finally, understand Python's exception hierarchy, raise your own exceptions, and write code that degrades gracefully instead of exploding.
~12 hrs try/exceptException hierarchyraiseCustom exceptionsfinallylogging -
09▾Modules, Packages, and Virtual EnvironmentsOrganizing code and managing dependencies
Write code that scales. Split logic into modules, build packages with __init__.py, use the standard library, and manage third-party packages with pip and venv. Understand import paths and avoid common module pitfalls.
~12 hrs importPackagespipvenvrequirements.txtStandard library -
10▾Comprehensions and Functional PatternsList, dict, set comprehensions, map, filter, zip
Write Python the Pythonic way. List comprehensions replace clunky loops. Dict comprehensions transform data. map(), filter(), and zip() enable functional programming patterns. Understand when to use each approach.
~13 hrs List comprehensionsDict comprehensionsSet comprehensionsmap()filter()zip() -
11▾Iterators, Generators, and Lazy EvaluationMemory-efficient sequences and the iterator protocol
Understand what actually happens when Python iterates. Build custom iterators with __iter__ and __next__, write generator functions with yield, and use itertools for powerful lazy sequences. Essential for large data and pipelines.
~15 hrs __iter__/__next__yieldGenerator expressionsitertoolsLazy evaluation
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12▾Working with External APIsrequests, REST APIs, authentication, and JSON
Connect your Python programs to the outside world. Use the requests library to hit REST APIs, handle authentication (API keys, OAuth), parse JSON responses, and build resilient API clients with retry logic.
~18 hrs requestsREST APIsJSON parsingAPI keysHTTP methodsError handling -
13▾Web Scraping with BeautifulSoupParsing HTML, extracting data, and automation basics
Extract data from the web when there's no API. Use BeautifulSoup to parse HTML, navigate the DOM, and extract structured data. Understand ethics and legal considerations. Introduction to Selenium for JavaScript-heavy sites.
~17 hrs BeautifulSoupHTML parsingCSS selectorsrequests-htmlScraping ethics -
14▾Data Analysis with pandasDataFrames, aggregation, and real-world data workflows
pandas is the workhorse of Python data work. Load CSV and Excel files into DataFrames, filter and transform data, group and aggregate, handle missing values, and export clean reports. Introduce matplotlib for basic visualization.
~18 hrs pandasDataFramegroupbymerge/joinmatplotlibMissing data -
15▾Testing with pytestUnit tests, fixtures, mocking, and test-driven development
Professional code ships with tests. Learn pytest from first test to full test suite: unit tests, parametrize, fixtures, mocking external dependencies, and measuring coverage. Introduction to TDD with a red-green-refactor exercise.
~17 hrs pytestassertFixturesMockingCoverageTDD -
16▾Command-Line Tools and Script Packagingargparse, Click, packaging, and distribution
Turn scripts into tools other people can use. Build CLI applications with argparse and Click, add --help docs, handle config files, and package your code for distribution with setuptools and PyPI.
~20 hrs argparseClickconfig filessetuptoolspyproject.tomlPyPI
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17▾Decorators and MetaprogrammingClosures, wrappers, class decorators, and __dunder__ mastery
Decorators are Python's superpower. Understand closures, write function and class decorators, use functools.wraps, and explore Python's data model through __getattr__, __setattr__, descriptors, and metaclasses.
~20 hrs Closures@decoratorfunctools.wrapsDescriptors__slots__Metaclasses -
18▾Concurrency — Threading and MultiprocessingParallel execution, the GIL, and when to use what
Make programs fast by running work in parallel. Understand the GIL and why it matters, use threading for I/O-bound tasks and multiprocessing for CPU-bound work. Build thread-safe data structures and avoid race conditions.
~20 hrs threadingmultiprocessingGILThreadPoolExecutorLocksQueue -
19▾Async Python with asyncioasync/await, event loops, and asynchronous I/O
Modern Python runs on async. Master the async/await syntax, understand event loops, use asyncio to run many I/O operations concurrently, and integrate async code with aiohttp for high-performance API calls.
~22 hrs async/awaitasyncioaiohttpEvent loopTasksgather() -
20▾Databases with SQLite and SQLAlchemySQL basics, ORMs, migrations, and data modelling
Persistent storage beyond files. Write SQL queries with sqlite3, map Python classes to database tables using SQLAlchemy ORM, handle migrations with Alembic, and model real-world relationships with foreign keys and joins.
~22 hrs SQLsqlite3SQLAlchemyORMAlembicRelationships -
21▾Capstone — Full Python ApplicationArchitecture, deployment, and professional code standards
Ship it. Bring together every part of the course into a polished, production-ready application. Apply type hints and mypy, set up CI with GitHub Actions, containerize with Docker, and write a README that a hiring manager would notice.
~21 hrs Type hintsmypyGitHub ActionsDockerLoggingREADME
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