Python and Other Technologies for Data Science
Lecture, three hours; discussion, one hour. Enforced requisite: course 20. Covers use of Python and other technologies for data analysis and data science. Focus on programming with Python and selection of its libraries: NumPy, pandas, matplotlib, and scikit-learn, for purpose of data processing, data cleaning, data analysis, and machine learning. Other technologies covered include Jupyter notebook and Git. Intended for Data Theory majors as introduction to Python language and libraries most frequently used in data science. Letter grading.
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Enrollment Progress
Mar 6, 3 PM PST
LEC 1: 71/70 seats taken (Full)
Section List
LEC 1
ClosedMWF 5pm-5:50pm
Online - Recorded
Course
Previous Grades
Grade distributions not available.