In this section, you'll learn about creating functions in Python, iterating over nested loops, and using basic statistics to measure aspects of different datasets.
We're going to spend most of this section deepening and widening your experience of programming in Python. We're going to introduce some of Python's built-in functions and methods, show you some more types of loops, and give you some practice of creating and using custom functions so you can efficiently reuse your code.
We're then going to take a break from coding by introducing some basic statistics - measures of centrality and dispersion - that will be crucial in understanding the datasets that you work with as a professional Data Scientist. We'll also get some more practice writing custom functions for calculating these statistics.
If you're already a professional software developer with a degree in a quantitative subject, it's not going to be the hardest section for you to complete. But please take the time to practice your skills and feel free to dig deeper with the optional "Level Up" content if you're done more quickly than your peers.
If you're completely new to coding and/or stats, you will probably find this a fairly challenging section. We're continuing to introduce core programming concepts at quite a pace. Don't worry if you still feel overwhelmed as you work through this section or work on the projects. You're going to get to practice most of these skills on a daily or weekly basis for the rest of the course!