Learning Path: Python

Learn about Python from start to finish

Rising in popularity alongside data science, it’s easy to forget that Python has a wide range of applications outside of crunching numbers and outputting graphs. This Learning Path will take you through a tour of the language from the fundamentals right up to more advanced patterns that help make your code more expressive, efficient and readable.

William Fiset

William Fiset is a Mathematics and Computer Science Honors student at Mount Allison University with in interest in competitive programming. William has been a Python developer for +4 years, starting his early Python experience with game development. He owns a popular YouTube channel that teaches Python to beginners and the basics of game development.

Daniel Arbuckle

Daniel Arbuckle holds a Doctorate in Computer Science from the University of Southern California, where he specialized in robotics and was a member of the nanotechnology lab. He now has more than ten years behind him as a consultant, during which time he’s been using Python to help an assortment of businesses, from clothing manufacturers to crowdsourcing platforms. Python has been his primary development language since he was in High School. He’s also an award-winning teacher of programming and computer science.

Prior exposure to basic Python syntax

Get to know Python’s data structures to enhance good design patterns and scalability to your code

Construct loops to perform repeated tasks

Create functions in Python to provide programs with better modularity

Understand the concept of function recursion adding clarity to write and debug codes

Manage program control flow and branching to perform conditional tasks

Install third-party libraries to add advanced customizations to images

Perform picture manipulations such as contrast and grayscale

Build Python packages to efficiently create reusable code

Become proficient at creating tools and utility programs in Python

Use the Git version control system to protect your development environment from unwanted changes

Harness the power of Python to automate other software

Distribute computation tasks across multiple processors

Handle high I/O loads with asynchronous I/O for smoother performance

Take advantage of Python's metaprogramming and programmable syntax features

Get to grips with unit testing to write better code, faster