Learning Python for Data Science

The class designed for you to learn to program without the stress of the test.

Spring 2021

INFORMATICS 490 (MH) is a programming class like no other on campus. Not only will you learn the Python programming language, but you'll also learn within the context of solving data driven problems (i.e. Data Science).

Unlike other programming classes, there is no need for coding experience, have a particular background or be enrolled in a specific major. INFO 490 teaches Python, software construction and problem decomposition without sacrificing important concepts, watering down material or using recipe-driven "boiler-plate" code. Regardless of your career or vocation, the ability to process and extract information from data programmatically (i.e. not using a GUI-driven program like Excel, Numbers, SPSS, etc) is a core skill in demand. You will be able to apply what you learn in this course to your other classes, your projects, and to your career.

What makes INFO 490 unique is that the entire class is taught online with a supporting set of tools that allow you to demonstrate mastery without your grade being solely dependent on the artificial stress of memorization and timed tests. Each topic taught has a set of test suites that allow you to practice until you pass. Feedback is immediate and you can re-submit updated solutions. You learn from doing and your effort and persistence are rewarded. You'll learn about the common structures of programming, the data processing pipeline, building modular code, text analysis, visualizations, test-driven development, and powerful data processing Python libraries like NumPy, Pandas, Matplotlib, NLTK, and SciPy.

Because INFO 490 is a graduate level class, it assumes you have competent time management skills and are comfortable participating in an online community. We do staff physical (and virtual) office hours and you can always meet with someone if you need additional assistance.

Prerequisites

Junior/Senior/Graduate Standing
Had at least 1 year of high school algebra
Comfortable reading to learn
Enjoy contributing and learning in an on-line environment