Introduction to Programming for Data Science

About the course

Linguists, chemists, business analysts, social scientists, and essentially everyone needs computational approaches to structure, analyze and present their data. However, non-experts are often intimidated to start programming and may struggle to see the numerous possibilities it may open up for their field of study. Using the popular and easy-to-learn Python language, this course offers a practical introduction to basics of programming and how it can be used to analyze, structure, and visualize data. Students will also gain hands-on experience with a number of popular libraries useful for data preparation and analysis.

What to expect

The course is structured as lectures with coding mini-sessions for immediate practice of programming concepts. There will be several graded programming assignments throughout the course. The students are expected to bring, set up, and use their own laptops, gradually building up a system that they can use after the course.

Course prerequisites: none.

Textbook: John V. Guttag, “Introduction to Computation and Programming Using Python: With Application to Understanding Data.” The MIT press, 2^nd ed., 2016

(The book will be available in RiverHawk bookshop by the start of the course)

Grading Scheme

Midterm: 30%

HW & four Programming assignments: 40%

Final exam: 30 %

Staff

Anna Rogers: arogers @ cs.uml.edu, Dandeneau 305

Office hours: T 2-3:30 pm, Th 2-3:30 pm

Anna Rumshisky: arum @ cs.uml.edu, Dandeneau 318

Office hours: TBA