Data Science, MS—Align (Boston)
Source: https://catalog.northeastern.edu/graduate/university-interdisciplinary-programs/data-science-align-ms-bos/ Parent: https://catalog.northeastern.edu/graduate/university-interdisciplinary-programs/
Complete all courses and requirements listed below unless otherwise indicated.
Students should refer to the course numbering table for graduate course leveling.
Align Bridge Coursework
Students are required to complete all bridge courses unless otherwise determined by the program.
A grade of B or higher is required in each course.
Course List
| Code | Title | Hours |
| --- | --- | --- | | Fundamentals | | | | CS 5001 and CS 5003 | Intensive Foundations of Computer Science and Recitation for CS 5001 | 4 | | Discrete Structures | | | | CS 5002 | Discrete Structures | 4 | | Programming for Data Science | | | | DS 5010 | Introduction to Programming for Data Science | 4 | | Additional Align Coursework | | | | DS 5020 | Introduction to Linear Algebra and Probability for Data Science | 4 |
Data Science Core
A cumulative GPA of 3.000 or higher is required in the following core courses.
Course List
| Code | Title | Hours |
| --- | --- | --- |
|---|---|---|
| Programming with Data | ||
| DS 5110 | Essentials of Data Science | 4 |
| Algorithms | ||
| CS 5800 | Algorithms | 4 |
| or EECE 7205 | Fundamentals of Computer Engineering | |
| Machine Learning | ||
| CS 6140 | Machine Learning | 4 |
| or EECE 5644 | Introduction to Machine Learning and Pattern Recognition | |
| Interdisciplinary Capstone | ||
| DS 5500 | Data Science Capstone | 4 |
Data Science Concentration Options
Complete one of the following concentrations:
- Computer Science—Khoury College of Computer Sciences
- Engineering Theory and Modeling—College of Engineering
Program Credit/GPA Requirements
40–48 total semester hours required\ Minimum 3.000 GPA required
Computer Science Concentration—Khoury College of Computer Sciences
Course List
| Code | Title | Hours |
| --- | --- | --- | | Complete 16 semester hours from the following: 1 | | 16 | | 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 | |
Engineering Theory and Modeling Concentration—College of Engineering
Course List
| Code | Title | Hours |
| --- | --- | --- | | Foundational Courses | | | | Complete 4 semester hours from the following: 1 | | 4 | | 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 | Data Mining in Engineering | | | IE 7280 | Statistical Methods in Engineering | | | Translational and Advanced Courses | | | | Complete the remaining 12 semester hours from the following: | | 12 | | 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 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 | Data Mining in Engineering | | | 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 | Neural Networks and Deep Learning | |
1 : Students taking electives worth less than 4 semester hours (i.e., Bouvé courses) should enroll for an accompanying data science project course in the same semester to bring the cumulative semester hours to 4. In order to earn this additional 1 semester 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.