Intermediate Data Programming

The world has become data-driven. Domain scientists and industry increasingly rely on data analysis to drive innovation and discovery; this reliance on data is not only restricted to science or business, but also is crucial to those in government, public policy, and those wanting to be informed citizens. As the size of data continues to grow, everyone will need to use powerful tools to work with that data.

This course teaches intermediate data programming. It is a follow-on to CSE122 (Introduction to Computer Programming II) or CSE160 (Data Programming).

The course complements CSE123 or CSE143, which focus more deeply on fundamental programming concepts and the internals of data structures. In contrast, CSE163 emphasizes the efficient use of those concepts for data programming.

In this course, students will learn:

1. More advanced programming concepts than in CSE122 or CSE160 including how to write bigger programs with multiple classes and modules.
2. How to work with different types of data: tabular, text, images, geo-spatial.
3. Ecosystem of data science tools including Jupyter Notebook and various data science libraries including scikit image, scikit learn, and Pandas data frames.
4. Basic concepts related to code complexity, efficiency of different types of data structures, and memory management.
5. Foundations of data literacy and technical communication for critical and conscientious data science.

This is class is designed as the second introductory programming course that focuses on writing programs that work with data. The prerequisites for the class require students having taken CSE 122/142 or CSE 160 and the class has been designed to be accessible to students from either of those backgrounds. Students that have taken 123/143 are welcome to take this class as it will serve as a complement to the material learned in 123/143 with only minor overlap.

Because this course will have students coming from many different class backgrounds, the first couple of weeks will be pretty different for students depending on what classes they have taken. Here is what we expect students to see in the first weeks based on their background:

• 122/142: The first two weeks might go pretty fast, but will be doable since you already know all the concepts (loops, conditionals, methods) and you are just learning all the new “words” in Python to use those concepts. This might require a little bit of extra practice early in the quarter so you are familiar with translating all the ideas you have learned in 142 to this new language. The first week has been designed to be a recap of all things 142 so you don’t also have to be learning a ton of new material while learning a new language in the first week.
• 160: The first week will just be a bit of a review for you, but the class will start covering material you haven’t seen before starting in the second week.
• 123/143: You are in a similar boat as the 122/142 students, where you know a lot of the concepts but don’t know the Python language. You’ll probably see a few things that you saw in 123/143 in this class, but I think the new context of processing data in a new language will still keep it new, exciting, and challenging.