DSCI 501 Quantitative Foundations of Data Science 3.0 Credits
Linear algebra, calculus, probability and statistical methods are essential foundation areas required for an effective understanding and application of data science. In this course, students will get a gentle introduction to these important areas of quantitative reasoning. Along with introducing basics of linear algebra, calculus, probability, and statistical methods, this course will also introduce their computational application through the Python programming language. Concepts will be demonstrated using various python packages.
College/Department: College of Computing and Informatics Repeat Status: Not repeatable for credit
In order to graduate, all students must pass three writing-intensive courses after their freshman year. Two writing-intensive courses must be in a student's major. The third can be in any discipline. Students are advised to take one writing-intensive class each year, beginning with the sophomore year, and to avoid “clustering” these courses near the end of their matriculation. Transfer students need to meet with an academic advisor to review the number of writing-intensive courses required to graduate.
For additional information, and an up-to-date list of the writing-intensive courses being offered, students should check the Drexel University Writing Center page