Programming for data scientists (Python)

Building on students’ programing background, this course delves into Python-specific programming. Basic language constructs are summarized, and then the focus moves to Python-specific sequence types: lists, tuples, strings, dictionaries, and arrays. NumPy, Pandas, Seaborn, and Scikit-learn libraries are used to tackle fundamental tasks of data science: cleaning, munging, aggregating, and visualizing data. With these Python tools, students will analyze time series data and create both linear and multiple linear regression models. Students’ learning will culminate in a final case study project, and if applicable, students are encouraged to use datasets relevant to their workplaces.

GR - Graduate

N - Course May Not Be Repeated