Program Overview:

Master of Science in Predictive Analytics Online

“Big Data.” You can find the term everywhere in the media tied to growth and innovation across the public and private sectors in nearly every major industry. But what does “Big Data” really mean? More importantly, how can organizations benefit from it? With new data acquisition technologies come vast new sources of data that can be analyzed to enhance organizational effectiveness, customer service, returns on investment, and a myriad of other business goals.


The Master of Science in Predictive Analytics (MSPA) program, established in 2011, is a fully online part-time graduate program, one of the first to offer dedicated training in data science. Fully accredited graduate-level courses cover business management and communications, information technology, and modeling. Small class sizes promote extensive online interaction among students and our elite faculty, who possess extensive education and business experience. Students gain critical skills for succeeding in today's data-intensive world, including business case study, data analysis, and making recommendations to management. They learn how to utilize database systems (SQL and NoSQL) and analytics software built upon R, Python, and SAS. They learn how to make trustworthy predictions using traditional statistics and machine learning methods. With a wide range of elective courses to choose from, students can customize their studies across a variety of data science disciplines, including marketing analytics, risk analytics, text analytics, and web and network data science. Special topic electives are offered each term, providing additional study opportunities, including decision analytics, financial market models and time series forecasting, sports analytics, geographical information systems, operations management, mathematical programming, simulation methods and analytics for total quality management. All courses are available in an asynchronous online format, with recorded lectures and tutorials. Find out more about online learning at SPS.

Predictive Analytics Faculty Perspective

Philip M. Goldfeder, PhD
Instructor in the MS in Predictive Analytics program and teaches mathematics and business courses at the undergraduate and graduate levels. Goldfeder's research and consulting experience includes predictive modeling to inform corporate mergers and acquisitions and evaluation of trends in automotive and spirits industries.

Program Goals

  • Articulate analytics as a core strategy
  • 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

Analytics 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.

Master of Science in Predictive Analytics (Northwestern University School of Professional Studies)
  • Online, part-time program
  • Builds expertise in advanced analytics, data mining, database management, financial analysis, predictive modeling, quantitative reasoning and web analytics, as well as 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)

Curriculum Requirements

Students are required to complete 12 courses to earn the degree. The curriculum covers eight core courses, two elective courses, a leadership or project management course, and a capstone (498) or thesis (590) project. Review curriculum details and elective choices while you consider applying to this program. Current students should refer to curriculum requirements in place at time of entry into the program.

Core Courses:

  • LEADERS 481-DL Leadership
  • PREDICT 400-DL Math for Modelers
  • PREDICT 401-DL Statistical Analysis
  • PREDICT 402-DL Analytics and Data Collection
  • PREDICT 410-DL Regression and Multi Analysis
  • PREDICT 411-DL Generalized Linear Models
  • PREDICT 413-DL Time Series and Forecasting
  • PREDICT 420-DL Database Systems
  • PREDICT 422-DL Practical Machine Learning
  • PREDICT 475-DL Project Management
  • PREDICT 498-DL Capstone Project
  • PREDICT 590-DL Thesis Research

Elective Courses:

  • PREDICT 412-DL Advanced Modeling Techniques
  • PREDICT 450-DL Marketing Analytics
  • PREDICT 451-DL Risk Analytics
  • PREDICT 452-DL Web Analytics
  • PREDICT 453-DL Text Analytics
  • PREDICT 455-DL Data Visualization
  • PREDICT 490-DL Special Topics