Python: Zero to Professional

We completed day one by exploring why Python is important and introducing the course, then installed the ide, uv, and Python, with an optional Jupyter setup.

Explore Google Colab, a browser-based python environment that runs code on Google's infrastructure without local setup. Use markdown and code cells to run Hello world.

Master Python fundamentals by naming and using variables, through dynamic typing and printing in Google Colab, showing assignment, value changes, and basic syntax.

Assign values to variables, overwrite them, and see how the last assignment determines the current value, with prints showing Tyson, Alex, and values flowing between variables.

Review day-2 progress by revisiting GitHub. Consolidate learning of variables, data types, and variable naming through hands-on coding and a final exercise, celebrating your second trophy.

Learn how Python control flow uses if, elif, and else with proper indentation; explore blocks, colon syntax, and practical examples like age-based decisions and printing multiple statements.

Explore for loops and while loops with illustrations: print each employee from a list, one by one, and prompt for a number, cast to integer, until it equals five.

We officially close day 3 by cementing control flows, including variables, data types, and conditional statements with loops, then prepare to learn functions and tackle the day 5 real-world project.

Learn to write modular Python code by defining and calling functions, using parameters and return values, and building reusable utility functions with the def keyword.

Recap day four by reviewing python functions, parameters vs arguments, and return values. Apply function best practices, explore side effects, and tackle a simple interest exercise for day five.

Learn how to store and manage data with Python lists and dictionaries, using indexed access, slicing, modification, and key-value retrieval.

Explore list operations in Python, including append, insert at a specific index, remove by value, pop by index, and length, using practical fruit examples.

Apply data structures—lists and dictionaries—to build a to-do list app, building on week 1 fundamentals of conditionals, loops, and functions; next, explore exception handling for robust code.

Demonstrate Python exception handling by wrapping division code in try/except, catching zero division errors, and printing a graceful invalid input message. Explore specific exceptions and when to let others propagate.

Apply exception handling to a real-world shopping cart checkout, validating inventory, stock, and item presence, while implementing custom exceptions and a complete checkout flow in Python.

Learn how classes and objects represent real world entities in Python, with a week 2 recap on dictionaries, lists, exception handling, and modular programming, highlighting progress toward upcoming projects.

Master Python fundamentals and advanced topics through week 1 concepts like variables and loops, and week 2 data structures and classes, as you complete day 4's weekly number guessing game.

Close out week 2 by completing the student grading system project, building on week 1 fundamentals—from variables and data types to control flows, functions, data structures, classes, and exception handling.

Explore file handling in Python by opening, reading, writing, and appending with safe context managers and error handling, then apply these concepts in a real-world scenario.

Use SQLite with Python to create databases, a cursor, and perform create, read, update, and delete operations with commits. Work with company.db and student.db toward an expense tracker project.

Recap the day three project with a log file analyzer handling a production web server log to count successful and failed entries and compute metrics for a concise report.

Learn to build a stock watcher project by calling the Massive.com real-time stock API in Python, fetch live prices, parse JSON, and display results.