Program Overview

Introduction to the Master of Science in Data Science Program

The Master of Science in Data Science program at Northwestern University School of Professional Studies requires the successful completion of 12 courses to obtain a degree. The program is designed to provide students with a comprehensive education in data science, including core courses, specialization courses, electives, and a thesis or capstone project.

Core Curriculum

The core curriculum consists of 8 courses that provide a foundation in data science. These courses include:

• MSDS 400-DL Math for Modelers
• MSDS 401-DL Applied Statistics with R
• MSDS 420-DL Database Systems
• MSDS 422-DL Practical Machine Learning
• MSDS 460-DL Decision Analytics
• MSDS 485-DL Data Governance, Ethics, and Law
• MSDS 498-DL Capstone or MSDS 590-DL Thesis
• One additional course from a list of options, including MSDS 402-DL Research Design for Data Science, MSDS 403-DL Data Science and Digital Transformation, MSDS 470-DL Technology Entrepreneurship, MSDS 472-DL Management Consulting, MSDS 474-DL Accounting and Finance for Technology Managers, MSDS 475-DL Project Management, MSDS 476-DL Business Process Analytics, and MSDS 480-DL Business Leadership and Communications

Elective Courses

In addition to the core curriculum, students must complete 2 elective courses from a list of options, including:

• MSDS 402-DL Research Design for Data Science
• MSDS 403-DL Data Science and Digital Transformation
• MSDS 410-DL Supervised Learning Methods
• MSDS 411-DL Unsupervised Learning Methods
• MSDS 413-DL Time Series Analysis and Forecasting
• MSDS 430-DL Python for Data Science
• MSDS 431-DL Data Engineering with Go
• MSDS 432-DL Foundations of Data Engineering
• MSDS 434-DL Analytics Application Engineering
• MSDS 436-DL Analytics Systems Engineering
• MSDS 440-DL Conversational AI Assistants
• MSDS 442-DL AI Agent Design and Development
• MSDS 450-DL Marketing Data Science
• MSDS 451-DL Financial Machine Learning
• MSDS 452-DL Web and Network Data Science
• MSDS 453-DL AI and Natural Language Processing
• MSDS 454-DL Applied Probability and Simulation Modeling
• 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 Knowledge Engineering
• MSDS 462-DL AI and Computer Vision
• MSDS 464-DL AI Systems and Robotics
• MSDS 466-DL Applied Generative AI for Enterprises
• MSDS 470-DL Technology Entrepreneurship
• MSDS 472-DL Management Consulting
• MSDS 474-DL Accounting and Finance for Technology Managers
• MSDS 475-DL Project Management
• MSDS 476-DL Business Process Analytics
• MSDS 480-DL Business Leadership and Communications
• MSDS 490-DL Special Topics in Data Science
• MSDS 491-DL Special Topics
• MSDS 499-DL Independent Study

Specializations

The program offers several specializations, including:

• Analytics and Modeling Specialization
• Analytics Management Specialization
• Artificial Intelligence Specialization
• Data Engineering Specialization
• Technology Entrepreneurship Specialization
• General Data Science Track

Analytics and Modeling Specialization

This specialization prepares data scientists to utilize algorithms for predictive modeling and analytics, developing models for marketing, finance, and other business applications. The specialization requires two courses:

• MSDS 410-DL Data Modeling for Supervised Learning
• MSDS 411-DL Data Modeling for Unsupervised Learning

Analytics Management Specialization

This specialization equips data scientists with the communication and management strategies needed to be data-driven leaders who utilize models, analyses, and statistical data to improve business performance. The specialization requires two courses:

• MSDS 474-DL Accounting and Finance for Technology Managers
• MSDS 476-DL Business Process Analytics

Artificial Intelligence Specialization

This specialization trains data scientists to implement solutions in computer vision, natural language processing, and software robotics. The specialization requires two courses:

• MSDS 453-DL AI and Natural Language Processing
• MSDS 458-DL Artificial Intelligence and Deep Learning

Data Engineering Specialization

This specialization trains data scientists to utilize system-wide problem-solving skills, choose hardware systems, and build software systems for implementing models made by data analysts to scale in productions systems. The specialization requires two courses:

• MSDS 432-DL Foundations of Data Engineering
• MSDS 434-DL Analytics Application Engineering

Technology Entrepreneurship Specialization

This specialization shows students the path to building a successful, innovation-driven startup. The specialization requires two courses:

• MSDS 470-DL Technology Entrepreneurship
• MSDS 474-DL Accounting and Finance for Technology Managers

General Data Science Track

Students seeking a less prescriptive curriculum may tailor elective coursework to their personal and professional needs. This generalist track is particularly useful for data scientists seeking employment with small businesses and smaller-scale projects, in which a single data scientist might have to serve as data analyst, data engineer, and analytics manager.

Final Project

As their final course in the program, students take either a master's thesis project in an independent study format or a classroom final project class in which students integrate the knowledge they have gained in the core curriculum in a team project approved by the instructor. The master's thesis or capstone class project count as one unit of credit. Students may choose one of the following:

• MSDS 498-DL Capstone Project
• MSDS 590-DL Thesis Research