Search Results
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.
Repeat Status: Not repeatable for credit
Data Science
http://catalog.drexel.edu/graduate/collegeofcomputingandinformatics/datascience/
...0 DSCI 501 3.0 DSCI 631 3.0 DSCI 632 3.0 DSCI 511...
Post-Baccalaureate Certificate in Applied Data Science
http://catalog.drexel.edu/graduate/collegeofcomputingandinformatics/applieddatasciencepbc/
...3.0 DSCI 501 3.0 Elective 3.0 DSCI 511 3.0 DSCI 521...
Post-Baccalaureate Certificate in Applied Artificial Intelligence/Machine Learning for Data Science
...Credits Winter Credits DSCI 501 3.0 DSCI 631 3.0 DSCI 521 3.0...