Introduction to Computer Science: Data
As our access to data and compute power have increased, more and more disciplines rely on computer science techniques to analyze, visualize, and process information. As such, coding skills and computational thinking are increasingly important for work in a wide variety of fields and disciplines. This course is an introduction to computer science, designed to teach students general computational skills and habits of mind that will be immediately useful and practical, and which will also prepare them for further study in computer science and related areas. Students who successfully complete this course will be able to: read a simple program and correctly describe the outcome, take a problem statement and convert it into code, and gain an understanding of how basic computer memory works and why this matters. Topics covered will include conditionals and loops, data types, functions, as well as higher-level concepts such as abstraction, version control, and debugging. The context for this class is data; students will learn how to import and generate data, manipulate and transform it, and visualize it.
This course is intended for students who have little to no computer experience and who are interested in learning the foundations of computer science through projects that require working with data. We will use examples in class and you will implement projects throughout the course where we both generate and use data coming from across the physical, natural, and social sciences. It will be helpful if you are interested in data, but no prior experience with any particular type of data is necessary.
The course is taught in Python. Students will be evaluated on weekly quizzes and weekly projects. This course, or the equivalent, is required for many further courses in computer science, machine learning, data science, robotics, and related areas.