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.
About the Author
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 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
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