Program Overview

Master's in Data Science Online

Data science has become an integral part of every major industry, changing the way organizations collect information, analyze data, and strategize for the future. Students in Northwestern’s online MS in Data Science program build the technical, analytical, and managerial expertise needed to address the practical problems of today's data-driven world.

Evolving Opportunities

As this interdisciplinary field continues to evolve, data scientists are defining new areas of focus to play key roles at various stages of the business cycle through modeling, engineering, and management. Consequently, professionals with expertise in data analysis, mathematics, machine learning, object-oriented programming, computer science, and business management are in demand across a wide range of industries.

About the Program

MSDS students gain critical skills for succeeding in today's data-intensive world. They learn how to utilize relational and document database systems and analytics software built upon open-source systems such as R, Python, and TensorFlow. They learn how to make trustworthy predictions using traditional statistics and machine learning methods.

MSDS faculty members include data scientists, professional researchers and consultants, social scientists, mathematicians, statisticians, and computer scientists. Most faculty members hold terminal doctoral degrees and have extensive teaching and business experience.

Students coming from non-technical backgrounds are welcome in MSDS program. Many courses are designed to help students make the transition from non-technical to technical studies. Early courses in the program include math for data scientists, statistical analysis, Python programming essentials, and introduction to data science.

The Master of Science in Data Science program is an extension of an already successful graduate program, the Master of Science in Predictive Analytics (MSPA) program, which was established in 2011. The MSPA program was one of the first programs in the world to offer dedicated graduate training in data science. The Master of Science in Data Science program includes all courses from the MSPA program, while adding seven new courses and three specializations.

Curriculum Overview

The Master's in Data Science requires the successful completion of 12 courses to obtain a degree. These requirements cover six core courses, a leadership or project management course, two required courses corresponding to a declared specialization, two electives, and a capstone project (498) or thesis (590). See below for core and elective courses.

Online Learning at Northwestern

The program uses an asynchronous model — meaning that students have no requirement to be online at any particular day of the week or time of day. As with other online programs at Northwestern, every course in the MSDS program has a maximum enrollment of 25 students. Courses utilize a variety of educational modalities, including video lectures, textbooks and handouts, discussion boards, programming assignments, case studies, team projects, quizzes and exams. Faculty and students are encouraged to be actively involved in courses, interacting with one another in a collaborative learning environment.

Find out more about online learning at SPS.

Choose the path that meets your needs

MSDS students may choose one of three specializations, or select elective courses to meet their specific needs.

  • The analytics management specialization draws on courses such as accounting and finance for analytics managers, project management, business leadership and communications, analytics consulting, and analytics entrepreneurship.
  • The analytics and modeling specialization draws on courses such as regression and multivariate analysis, generalized linear models, time series analysis and forecasting, practical machine learning, and advanced modeling techniques.
  • The data engineering specialization draws courses such as database systems and data preparation, foundations of data engineering, analytics application development, and analytics systems analysis.

With a wide range of elective courses to choose from, students can customize their studies across a variety of data science disciplines, including, for example, marketing analytics, financial and risk analytics, text analytics, web and network data science, and artificial intelligence and deep learning. Students interested in sports analytics have the option of taking electives in sports performance analytics and sports management analytics.

Program Goals

  • Articulate analytics as a core strategy of data science
  • Transform data into actionable insights
  • Develop statistically sound and robust analytic solutions
  • Demonstrate leadership
  • Formulate and manage plans to address business issues
  • Evaluate constraints on the use of data
  • Assess data structure and data lifecycle

Data Science Master's Programs at Northwestern

Northwestern University offers two master’s degree programs in analytics that prepare students to meet the growing demand for data-driven leadership and problem solving. In addition to the online MSDS program, Northwestern's McCormick School of Engineering offers a full-time on-campus program.

Master of Science in Data Science (Northwestern University School of Professional Studies)

  • Online, part-time program
  • Builds expertise in advanced analytics, data mining, database management, financial analysis, predictive modeling, data engineering, quantitative reasoning and web analytics, analytics management, and advanced communication and leadership.

Master of Science in Analytics (McCormick School of Engineering and Applied Science)
  • 15-month, full-time, on-campus program
  • Integrates data science, information technology and business applications into three areas: predictive (forecasting), descriptive (business intelligence and data mining) and prescriptive (optimization and simulation)

Core Courses:

  • MSDS 400-DL Math for Data Scientists
  • MSDS 401-DL Statistical Analysis
  • MSDS 402-DL Introduction to Data Science
  • MSDS 420-DL Database Systems and Data Preparation
  • MSDS 422-DL Practical Machine Learning
  • MSDS 460-DL Decision Analytics
  • MSDS 475-DL Project Management
  • MSDS 480-DL Business Leadership and Communications
  • MSDS 498-DL Capstone Project
  • MSDS 590-DL Thesis Research

Elective Courses:

  • MSDS 410-DL Regression and Multivariate Analysis
  • MSDS 411-DL Generalized Linear Models
  • MSDS 413-DL Time Series Analysis and Forecasting
  • MSDS 430-DL Python for Data Science
  • MSDS 432-DL Foundations of Data Engineering
  • MSDS 434-DL Analytics Application Development
  • MSDS 436-DL Analytics Systems Analysis
  • MSDS 450-DL Marketing Analytics
  • MSDS 451-DL Financial and Risk Analytics
  • MSDS 452-DL Web and Network Data Science
  • MSDS 453-DL Text Analytics
  • MSDS 454-DL Advanced Modeling Techniques
  • MSDS 455-DL Data Visualization
  • MSDS 456-DL Sports Performance Analytics
  • MSDS 457-DL Sports Management Analytics
  • MSDS 458-DL Artificial Intelligence and Deep Learning
  • MSDS 459-DL Information Retrieval and Real-Time Analytics
  • MSDS 470-DL Analytics Entrepreneurship
  • MSDS 472-DL Analytics Consulting
  • MSDS 474-DL Accounting and Finance for Analytics Managers
  • MSDS 490-DL Special Topics in Data Science