Math for Data Science Certificate Program

For students and professionals seeking to build math and analysis proficiency, the Math for Data Science post-baccalaureate certificate program is designed to strengthen their quantitative background for graduate school or to enhance their data analysis skills for their careers. Consisting of courses in applied mathematics, statistics, and calculus, the program provides students with a quantitative foundation for data analysis—a critical skillset that is applicable to a wide range of industries.

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About the Math for Data Science Program

Math for Data Science Goals and Courses

Math for Data Science Tuition

Post-baccalaureate students at Northwestern's School of Professional Studies pay per course. For more information about financial obligations and tuition, please visit the Tuition page.

Admission for Math for Data Science

In addition to completing an online application, you'll also need to submit a few supplemental materials. A list of requirements for admission including application deadlines and tips on how to apply can be found at the Admission page.

Math for Data Science Registration Information

Whether you're a first-time registrant or current and returning student, all students register using our online student registration and records systems. Important information about registering for courses at SPS, including registration timelines and adding or dropping courses in which you are already enrolled, can be found on the Registration Information page.

Find out more about the Math for Data Science Program

Program Courses:Course Detail
Finite Mathematics <> MATH 202-CN

This course is a foundation of mathematical knowledge targeting data analysis, and covers selected topics from elementary linear algebra and its applications to linear optimization problems, finite probability, and elementary statistics. Prerequisite: none.

 

 


View MATH 202-CN Sections
Single-Variable Differential Calculus <> MATH 220-A

This course covers the following: limits; differentiation; linear approximation and related rates; extreme value theorem, mean value theorem, and curve-sketching; optimization. This course was formerly MATH 220-CN.


View MATH 220-A Sections
Single-Variable Differential Calculus <> MATH 220-A-DL

This course covers the following: limits; differentiation; linear approximation and related rates; extreme value theorem, mean value theorem, and curve-sketching; optimization. Through this course students will explore, tangle with, and ultimately master the fundamental techniques of differential calculus, all of which stem from the limit and all of which revolve around wielding the derivative as a powerful tool for understanding the mathematical and physical world. The course is conducted completely online. A technology fee will be added to tuition. Prerequisite: a solid foundation in algebra, trigonometry, and geometry. This course was formerly MATH 220-CN.


View MATH 220-A-DL Sections
Single-Variable Integral Calculus <> MATH 220-B

This course covers the following: definite integrals, antiderivatives, and the fundamental theorem of calculus; transcendental and inverse functions; areas and volumes; techniques of integration, numerical integration, and improper integrals; first-order linear and separable ordinary differential equations. Prerequisite: MATH 220-A. This course was formerly MATH 224-CN.


View MATH 220-B Sections
Multivariable Differential Calculus <> MATH 230-A

This course covers the following: vectors, vector functions, partial derivatives, and optimization. Prerequisite: MATH 220-B. This course was formerly MATH 230-CN.

As of 9/15/21, this course has been cancelled.


View MATH 230-A Sections
Linear Algebra <> MATH 240-CN

This course covers basic concepts of linear algebra: solutions of systems of linear equations; vectors and matrices; subspaces, linear independence, and bases; determinants; eigenvalues and eigenvectors; other topics and applications as time permits.nPrerequisite: MATH 230-A or MATH 230 (former), or equivalent.



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Introduction to Statistics <> STAT 202-CN

This course is intended to familiarize students with the basics of statistics as a baseline for academic and/or professional application. Topics include (but are not limited to) basic descriptive statistics, data testing, correlations, analyses of variance, and regression analysis. The course will include instruction on how to use Excel to help students perform statistical analyses for future problem-solving and decision-making. Basic knowledge of algebra is recommended.


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Introduction to Statistics STAT 202-DL

This course provides an introduction to probability and statistics theory. Assignments and projects help develop students’ analytic and critical thinking skills and challenge them to apply statistical analysis with real world data. The course contains three parts: methods of data collection, techniques for data organization and analysis, and techniques for interpreting data using statistical methodologies. Students will learn not only how to appropriately collect and analyze data, but how to draw conclusions from their data for use in decision-making. The course emphasizes use of Microsoft Excel for graphing and data analysis in homework assignments. Students will also collect and analyze a data set of personal interest for the final project. A final paper will also be prepared. Microsoft Excel and PowerPoint techniques relevant to the final project will be taught in class, however, a basic understanding of these applications is expected. This course is conducted completely online. A technology fee will be added to tuition.


View STAT 202-DL Sections