The Master of Science in Data Science delivers a comprehensive framework for processing, modeling, analyzing, and reasoning about data.
An extensive core curriculum—designed jointly by College of Computer and Informations Sciences and Department of Electrical and Computer Engineering faculty—enables you to develop depth in computational modeling, data collection and integration, data storage and retrieval, data processing, modeling and analytics, and visualization. Plus, electives from CCIS, the College of Engineering, or a Northeastern partner college provide an opportunity to explore key contextual areas or more complex technical applications.
Courses are tailored toward technically or mathematically trained students
Elective courses are available from seven colleges throughout the University, including D'Amore-McKim School of Business, the College of Arts, Media and Design, and the College of Social Sciences and Humanities
The Data Science MS degree empowers you to:
Attain data scientist and data engineer positions in a fast-growing field
Learn how our teaching and research benefit from a worldwide network of students, faculty and industry partners.
A grade of B or higher is required in the following courses:
Complete 4 semester hours from the following:
CS 5800 - Algorithms
EECE 7205 - Fundamentals of Computer Engineering
Data Management and Processing
DS 5110 - Introduction to Data Management and Processing
Machine Learning and Data Mining
DS 5220 - Supervised Machine Learning and Learning Theory
DS 5230 - Unsupervised Machine Learning and Data Mining
Presentation and Visualization
Complete 12 semester hours from the following:
College of Computer and Information Science
CS 6200 - Information Retrieval
CS 5100 - Foundations of Artificial Intelligence
CS 6120 - Natural Language Processing
CS 5750 - Social Computing
CS 6350 - Empirical Research Methods
CS 7180 - Special Topics in Artificial Intelligence
CS 7280 - Special Topics in Database Management
College of Engineering
CIVE 7388 - Special Topics in Civil Engineering
2.00 - 4.00
EECE 5639 - Computer Vision
EECE 5640 - High-Performance Computing
EECE 7335 - Detection and Estimation Theory
EECE 7337 - Information Theory
EECE 7360 - Combinatorial Optimization
EECE 7370 - Advanced Computer Vision
EECE 7397 - Advanced Machine Learning
IE 5640 - Data Mining for Engineering Applications
IE 7275 - Data Mining in Engineering
IE 7280 - Statistical Methods in Engineering
College of Social Sciences and Humanities
PPUA 5261 - Dynamic Modeling for Environmental Decision Making
PPUA 5262 - Big Data for Cities
PPUA 5263 - Geographic Information Systems for Urban and Regional Policy
PPUA 5266 - Urban Theory and Science
PPUA 7237 - Advanced Spatial Analysis of Urban Systems
POLS 7200 - Perspectives on Social Science Inquiry
POLS 7201 - Research Design
POLS 7202 - Quantitative Techniques
D'Amore-McKim School of Business
BUSN 6320 - Business Analytics Fundamentals
BUSN 6324 - Predictive Analytics for Managers
BUSN 6326 - Introduction to Big Data and Digital Marketing Analytics
College of Science
MATH 7340 - Statistics for Bioinformatics
PHYS 5116 - Complex Networks and Applications
PHYS 7305 - Statistical Physics
PHYS 7321 - Computational Physics
PHYS 7331 - Network Science Data
Bouve College of Health Sciences
NRSG 5121 - Epidemiology and Population Health
PHTH 5202 - Introduction to Epidemiology
PHTH 5210 - Biostatistics in Public Health
PHTH 5224 - Social Epidemiology
College of Arts, Media, and Design
GSND 5110 - Game Design and Analysis
GSND 6350 - Game Analytics
Note: Students that take 3-credit-hour elective courses (ie Bouve, CSSH courses) will register for an accompanying data science project course in the same semester ((DS 8982)). In order to earn this additional credit, students will be 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.
Co-op makes the Northeastern graduate education richer and more meaningful. It provides Master’s students with up to twelve months of professional experience that helps them develop the knowledge, awareness, perspective, and confidence to develop rich careers. In addition to the esteemed faculty, many students enroll in the Master’s programs largely because of the successful Co-op Program.
Graduate students typically have an experiential work opportunity following their second semester. This could be a 6-8 month co-op or a 3-4 month summer internship. Those who initially experience co-op may have the opportunity to seek an internship for the following summer, or vice versa.
Student participation in experiential education provides enhanced:
Maturity, responsibility, and self-knowledge
Job seeking and job success skills
Networking opportunities with those in desired career paths
Northeastern’s Co-op Program is based on a unique educational strategy which recognizes that classroom learning only provides some of the skills students will need to succeed in their professional lives. Our administration, faculty and staff are dedicated to the university’s mission to “educate students for a life of fulfillment and accomplishment.” Co-op is closely integrated with our course curriculum and our advising system. The team of Graduate Co-op Faculty within the College of Computer and Information Science provides support for students in preparing for and succeeding on their co-ops.
These multiple connections make co-op at Northeastern an avenue to intellectual and personal growth: adding depth to classroom studies, providing exposure to career paths and opportunities, and developing in students a deeper understanding that leads to success in today’s world.
Our faculty represents a wide cross-section of professional practices and in fields ranging from finance to education to biomedical science to management to the U.S. military. They serve as mentors and advisors, and collaborate alongside students to solve the most pressing global challenges facing established and emerging markets.
By enrolling in Northeastern, you gain access to a network of more than 230,000 alumni and 3,000 employer partners, including Fortune 500 companies, government agencies, and global NGOs. Our current students and faculty across strategically located regional campuses further foster that lifelong global community of learning and mentoring.
Below is a look at where our Computing & IT alumni work, the positions they hold, and the skills they bring to their organization.