Data Science, MS (Boston)

Graduatemajor2027 catalogUniversity Interdisciplinary ProgramsBoston32 semester hours totalverified parse

Official catalog page for this program

Programming with Data

• DS 5110 — Essentials of Data Science

Algorithms

• One of:
  • CS 5800 — Algorithms
  • EECE 7205 — Fundamentals of Computer Engineering

Machine Learning

• One of:
  • CS 6140 — Machine Learning
  • EECE 5644 — Introduction to Machine Learning and Pattern Recognition

Interdisciplinary Capstone

• DS 5500 — Data Science Capstone

Concentrations (choose 1)

Computer Science

From the catalog

Complete 16 semester hours from the following:

• Choose 16 semester hours from:
  • CS 5100 — Foundations of Artificial Intelligence
  • CS 5180 — Reinforcement Learning and Sequential Decision Making
  • CS 5200 — Database Management Systems
  • CS 5330 — Pattern Recognition and Computer Vision
  • CS 5340 — Computer/Human Interaction
  • CS 5610 — Web Development
  • CS 6120 — Natural Language Processing
  • CS 6200 — Information Retrieval
  • CS 6220 — Data Mining Techniques
  • CS 6240 — Large-Scale Parallel Data Processing
  • CS 6350 — Empirical Research Methods
  • CS 6620 — Fundamentals of Cloud Computing
  • CS 6650 — Building Scalable Distributed Systems
  • CS 7140 — Advanced Machine Learning
  • CS 7150 — Deep Learning
  • CS 7180 — Special Topics in Artificial Intelligence
  • CS 7200 — Statistical Methods for Computer Science
  • CS 7250 — Information Visualization: Theory and Applications
  • CS 7280 — Special Topics in Database Management
  • CS 7290 — Special Topics in Data Science
  • CS 7990 — Thesis
  • CS 8674 — Master’s Project
  • DS 7995 — Project
• One of:
  • CS 6964 — Co-op Work Experience
  • CS 6954 — Co-op Work Experience - Half-Time
  • CS 6955 — Co-op Work Experience Abroad - Half-Time
  • CS 6965 — Co-op Work Experience Abroad

Data Design and Visualization

From the catalog

Complete 8 semester hours from the following:

• Choose 8 semester hours from:
  • ARTG 5150 — Information Visualization Principles and Practices
  • ARTG 5151 — Information Design Critique Seminar
  • ARTG 5330 — Visualization Technologies 1: Fundamentals

• From the catalog

  Complete 8 semester hours from the following:

• Choose 8 semester hours from:
  • ARTG 5110 — Information Design History
  • ARTG 5130 — Visual Communication for Information Design
  • ARTG 5310 — Visual Cognition
  • ARTG 5430 — Visualization Technologies 2: Advanced Practices
  • ARTG 6110 — Information Design Theory and Critical Thinking
  • ARTG 6330 — Information Design Mapping Strategies
  • CS 5340 — Computer/Human Interaction
  • CS 5610 — Web Development
  • CS 7250 — Information Visualization: Theory and Applications
  • EECE 5642 — Data Visualization
  • GSND 6340 — Biometrics of Design
  • GSND 6350 — Data-Driven Game Design
  • IE 6600 — Computation and Visualization for Analytics
• One of:
  • EEAM 6964 — Co-op Work Experience
  • EEAM 6954 — Co-op Work Experience - Half-Time
  • EEAM 6955 — Co-op Work Experience Abroad - Half-Time
  • EEAM 6965 — Co-op Work Experience Abroad

Engineering Theory and Modeling

From the catalog

Complete 4 semester hours from the following:

Complete the remaining 12 semester hours from the following:

Complete the following (students must complete ENCP 6100 to qualify for co-op experience):

• Choose 4 semester hours from:
  • DS 7995 — Project
  • EECE 5360 — Combinatorial Optimization
  • EECE 5612 — Statistical Inference: An Introduction for Engineers and Data Analysts
  • EECE 7204 — Applied Probability and Stochastic Processes
  • EECE 7323 — Numerical Optimization Methods
  • EECE 7337 — Information Theory
  • EECE 7346 — Probabilistic System Modeling and Analysis
  • IE 6400 — Foundations for Data Analytics Engineering
  • IE 7275 — Machine Learning and Data Analytics
  • IE 7280 — Statistical Methods in Engineering
• Choose 12 semester hours from:
  • BIOE 5750 — Modeling and Inference in Bioengineering
  • BIOE 5880 — Computational Methods in Systems Bioengineering
  • BIOE 6200 — Mathematical Methods in Bioengineering
  • CHME 5137 — Computational Modeling in Chemical Engineering
  • CHME 5649 — Numerical Strategies and Data Analytics for Chemical Sciences
  • CIVE 7100 — Time Series and Geospatial Data Sciences
  • CIVE 7150 — Data-Driven Decision Support for Civil and Environmental Engineering
  • EECE 5360 — Combinatorial Optimization
  • EECE 5612 — Statistical Inference: An Introduction for Engineers and Data Analysts
  • EECE 5614 — Reinforcement Learning and Decision Making Under Uncertainty
  • EECE 5626 — Image Processing and Pattern Recognition
  • EECE 5639 — Computer Vision
  • EECE 5640 — High-Performance Computing
  • EECE 5642 — Data Visualization
  • EECE 5645 — Parallel Processing for Data Analytics
  • EECE 5668 — Large Language Models
  • EECE 7204 — Applied Probability and Stochastic Processes
  • EECE 7215 — Introduction to Distributed Intelligence
  • EECE 7223 — Riemannian Optimization
  • EECE 7323 — Numerical Optimization Methods
  • EECE 7337 — Information Theory
  • EECE 7345 — Big Data and Sparsity in Control, Machine Learning, and Optimization
  • EECE 7346 — Probabilistic System Modeling and Analysis
  • EECE 7370 — Advanced Computer Vision
  • EECE 7397 — Advanced Machine Learning
  • EECE 7945 — Master’s Project
  • IE 5137 — Computational Modeling in Industrial Engineering
  • IE 5390 — Structured Data Analytics for Industrial Engineering
  • IE 5630 — Biosensor and Human Behavior Measurement
  • IE 5640 — Data Mining for Engineering Applications
  • IE 6400 — Foundations for Data Analytics Engineering
  • IE 6600 — Computation and Visualization for Analytics
  • IE 6700 — Data Management for Analytics
  • IE 6750 — Data Warehousing and Integration
  • IE 7270 — Intelligent Manufacturing
  • IE 7275 — Machine Learning and Data Analytics
  • IE 7280 — Statistical Methods in Engineering
  • IE 7295 — Applied Reinforcement Learning in Engineering
  • IE 7300 — Statistical Learning for Engineering
  • IE 7500 — Applied Natural Language Processing in Engineering
  • IE 7615 — Deep Learning for AI
• ENCP 6100 — Introduction to Cooperative Education
• One of:
  • ENCP 6964 — Co-op Work Experience
  • ENCP 6954 — Co-op Work Experience - Half-Time
  • ENCP 6955 — Co-op Work Experience Abroad - Half-Time
  • ENCP 6965 — Co-op Work Experience Abroad

GPA requirements

• Minimum 3.000 GPA required

Substitutions

Stated by the catalog on this program's requirements:

• Students who select electives that carry fewer than 4 semester hours of credit should enroll in Project (DS 7995) during the same term to complete an accompanying data science project. In order to earn this additional credit hour, students are expected to work with faculty to design an additional project in line with the curricular aims of their chosen elective and the data science core learning outcomes.

Possible equivalents for this program beyond the above — dashed means a suggestion, not a rule, and every substitution needs your advisor's approval:

• CS 6140 ↔ EECE 5644 (tier C)

What the tiers mean

Parsed from the catalog by NU Map; the structured machine copy is in this college's JSON for the 2027 catalog, under data-science-ms-boston, and the official page is the authority.