OrglobalAcademy

Course

Python Programming

A 12-week hands-on Python course where you write real code from day one and ship a project to GitHub every single week. Master the fundamentals — variables, control flow, data structures, functions, files, and object-oriented programming — then put them to work: calling live APIs and scraping the web, analyzing real datasets with pandas, automating Excel reports and repetitive tasks, testing with pytest, and building a small FastAPI web service. You finish with a free-choice capstone — a CLI tool, automation suite, data report, or API — presented and defended like a professional, plus a GitHub portfolio of 12 working projects. No prior programming experience required; expect 10–15 hours per week of lessons, labs, and a weekly project.

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Module 1 — Week 1 — Setup & First Programs

  1. ✓Why Python & setting up your machine
    25mFree preview
  2. ✓The terminal & the Python REPL
    25mFree preview
  3. ✓Variables & core types
    30mFree preview
  4. ✓Strings, input & output
    25mFree preview
  5. ✓Lab: install, verify & first script
    60mPracticalFree preview
  6. ✓Lab: Mad Libs & a receipt printer
    75mPracticalFree preview
  7. ✓Weekly project: unit & currency converter
    150mProjectFree preview

Module 2 — Week 2 — Control Flow

  1. ✓Making decisions: if, elif, else
    30m🔒
  2. ✓Loops: while & for
    30m🔒
  3. ✓Boolean logic, break & continue
    30m🔒
  4. ✓Think before you type: pseudocode
    25m🔒
  5. ✓Lab: number guessing game
    60mPractical🔒
  6. ✓Lab: loop drills
    75mPractical🔒
  7. ✓Weekly project: ATM simulator
    165mProject🔒

Module 3 — Week 3 — Data Structures

  1. ✓Lists & tuples
    30m🔒
  2. ✓Dictionaries: the most useful structure in Python
    30m🔒
  3. ✓Sets & choosing the right structure
    25m🔒
  4. ✓Slicing & comprehensions
    25m🔒
  5. ✓Lab: shopping cart drills
    70mPractical🔒
  6. ✓Lab: word frequency counter
    60mPractical🔒
  7. ✓Weekly project: contact book
    165mProject🔒

Module 4 — Week 4 — Functions, Modules & Git

  1. ✓Functions: name your logic
    25m🔒
  2. ✓Scope, defaults & flexible arguments
    25m🔒
  3. ✓Modules, pip & virtual environments
    30m🔒
  4. ✓Git & GitHub: your code, safe and public
    30m🔒
  5. ✓Lab: refactor the ATM into functions
    60mPractical🔒
  6. ✓Lab: your GitHub portfolio begins
    90mPractical🔒
  7. ✓Weekly project: expense splitter
    150mProject🔒

Module 5 — Week 5 — Files & Errors

  1. ✓Reading & writing files
    30m🔒
  2. ✓CSV: spreadsheets for programs
    25m🔒
  3. ✓JSON: saving structured data
    25m🔒
  4. ✓Exceptions: crash on purpose, recover on purpose
    30m🔒
  5. ✓Lab: notes app & log reader
    75mPractical🔒
  6. ✓Lab: CSV sales report
    75mPractical🔒
  7. ✓Weekly project: persistent expense tracker
    165mProject🔒

Module 6 — Week 6 — Object-Oriented Programming

  1. ✓Classes & objects: data with behavior attached
    30m🔒
  2. ✓Methods & dunder methods
    30m🔒
  3. ✓Inheritance vs composition
    30m🔒
  4. ✓Dataclasses & when not to use OOP
    25m🔒
  5. ✓Lab: model a shop
    75mPractical🔒
  6. ✓Lab: refactor the expense tracker
    90mPractical🔒
  7. ✓Weekly project: inventory manager
    180mProject🔒

Module 7 — Week 7 — The Standard Library & Real CLI Tools

  1. ✓datetime & random: time and chance
    28m🔒
  2. ✓The filesystem: os, shutil & pathlib together
    27m🔒
  3. ✓Regular expressions: enough to be dangerous
    30m🔒
  4. ✓argparse: CLIs with flags like a real tool
    25m🔒
  5. ✓Lab: extract phones & prices
    60mPractical🔒
  6. ✓Lab: timestamped backup script
    75mPractical🔒
  7. ✓Weekly project: file organizer CLI
    150mProject🔒

Module 8 — Week 8 — APIs & Web Scraping

  1. ✓How the web talks: HTTP in plain language
    25m🔒
  2. ✓requests: calling real APIs
    28m🔒
  3. ✓Web scraping with BeautifulSoup
    30m🔒
  4. ✓API keys, secrets & scraping ethics
    26m🔒
  5. ✓Lab: call a public API
    60mPractical🔒
  6. ✓Lab: scrape headlines
    60mPractical🔒
  7. ✓Weekly project: live exchange-rate CLI
    165mProject🔒

Module 9 — Week 9 — Data Analysis with pandas

  1. ✓Jupyter notebooks & a taste of numpy
    27m🔒
  2. ✓pandas: DataFrames & first look at data
    30m🔒
  3. ✓Cleaning real-world data
    30m🔒
  4. ✓Groupby & charts that answer questions
    28m🔒
  5. ✓Lab: your first notebook
    60mPractical🔒
  6. ✓Lab: clean the messy sales file
    90mPractical🔒
  7. ✓Weekly project: data analysis report
    180mProject🔒

Module 10 — Week 10 — Automation: Scripts That Save Hours

  1. ✓The automation mindset
    25m🔒
  2. ✓Excel automation with openpyxl
    30m🔒
  3. ✓Sending email & building reports
    30m🔒
  4. ✓Scheduling: run it while you sleep
    25m🔒
  5. ✓Lab: monthly sales report generator
    75mPractical🔒
  6. ✓Lab: schedule a script
    60mPractical🔒
  7. ✓Weekly project: automate an hour of your week
    150mProject🔒

Module 11 — Week 11 — Shipping Quality Code: Testing, Structure & FastAPI

  1. ✓Debugging like a professional
    30m🔒
  2. ✓Testing with pytest: proof your code works
    30m🔒
  3. ✓Project structure, README & docs that get you hired
    25m🔒
  4. ✓FastAPI: your code as a web service
    30m🔒
  5. ✓Lab: test the expense tracker
    75mPractical🔒
  6. ✓Lab: build a small API
    75mPractical🔒
  7. ✓Weekly project: a tested, documented service
    165mProject🔒

Module 12 — Week 12 — Capstone: Build, Review & Present

  1. ✓Scoping a capstone that actually ships
    30m🔒
  2. ✓Lab: build sprint
    90mPractical🔒
  3. ✓Lab: peer code review clinic
    90mPractical🔒
  4. ✓Career pathways & what to learn next
    30m🔒
  5. ✓Capstone: build, document & present
    240mProject🔒

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