12-Week Python Learning Timeline
Week 0 (setup, 2–3 hrs)
Install: Python 3.x, VS Code/PyCharm, Git.
Learn how to: run scripts, use venv, install packages with pip.
Mini task: print “Hello, <your name>”, read an input, and write to a text file.
Week 1 — Core syntax & mental model
Topics: variables, numbers/strings/booleans, if/elif/else, for/while, input(), print().
Do: 25–40 short exercises.
Build: CLI unit converter (°C↔°F, km↔mi, INR↔USD).
Week 2 — Functions & problem solving
Topics: functions, parameters/return, scope, type hints, docstrings.
Build: calculator with history stored in a file.
Week 3 — Data structures & files
Topics: lists, tuples, sets, dicts, slicing, comprehensions, file handling.
Build: contact book stored as JSON.
Week 4 — The Standard Library & testing
Libraries: datetime, random, math, statistics, json.
Testing: intro to pytest.
Build: notes CLI with autosave + tests.
Week 5 — OOP in Pythonic style
Topics: classes, objects, @dataclass, inheritance vs. composition.
Build: inventory system with @dataclass + tests.
Week 6 — Iteration, generators & context managers
Topics: iterators, yield, itertools, functools, context managers.
Build: log parser for large files using generators.
Week 7 — Working with the web
Topics: APIs with requests/httpx, JSON, simple auth.
Build: API aggregator (weather/crypto/news).
Week 8 — Concurrency & performance basics
Topics: threading, multiprocessing, asyncio basics.
Build: concurrent file downloader with performance test.
Weeks 9–12: Choose ONE specialization path
Path A — Web Apps (Flask/FastAPI)
Learn routing, templates, APIs, databases with SQLAlchemy.
Capstone: CRUD app (e.g., “TaskFlow”) with deploy.
Path B — Data, Analysis & Viz
Learn NumPy, pandas, Matplotlib, cleaning, EDA.
Capstone: publish a data report notebook with visuals.
Path C — Automation, Scripting & DevOps
Learn regex, CLI tools, logging, task scheduling, bots.
Capstone: “Daily Ops Bot” collecting and reporting data.
By following this structured 12-week roadmap, you will progress from the very basics of Python to creating practical, real-world projects. Each week builds on the previous one, combining theory, exercises, and hands-on projects so you not only understand the concepts but also apply them effectively. By the end of this path, you will be confident in Python fundamentals and ready to specialize in web development, data science, or automation, depending on your career goals. Remember: consistency is the key dedicate regular hours weekly, build small but meaningful projects, and keep your code organized in a portfolio. This journey can open doors to endless opportunities in programming and technology.
