Data Science

STEM Designation: This program is STEM (science, technology, engineering, and math)-designated by the Department of Homeland Security. For more information, please see https://www.newhaven.edu/admissions/stem-designated-programs.php

The Master of Science in Data Science (MSDS) program is designed to prepare students for opportunities and challenges in the field of data science. The program offers a strong foundation in data analysis, machine learning, artificial intelligence, and statistical modeling. Specialized focus areas include big data, deep learning, computer vision, and natural language processing with opportunities to gain subject matter expertise in a wide range of cross-disciplinary fields such as security, business analytics, and health care analytics. To earn the MSDS degree, a student must complete a minimum of 33 credits.

Program Outcomes:

1. Perform explorative data analysis in the context of real world applications.
2. Design and build appropriate algorithms to model and interpret data.
3. Build an end-to-end distributed data-pipeline.
4. Apply subject-matter expertise to the design and development of data-driven solutions.
5. Demonstrate the ability to work independently.

Required Courses (21 credits)

• DSCI 6001 - Math for Data Scientists
• DSCI 6002 - Introduction to Data Science
• DSCI 6003 - Machine Learning
• DSCI 6004 - Natural Language Processing
• DSCI 6007 - Distributed & Scalable Data Engineering
• DSCI 6011 - Deep Learning
• DSCI 6612 - Introduction to Artificial Intelligence

Internship or Capstone (3 credits)

• DSCI 6010 - Data Science Internship

• or

• DSCI 6051 - Data Science Capstone Project

Special Topics and Electives

Choose two courses including at least one from Special Topics.  Students can take either two Special Topics or one Special Topics and one Elective.

Special Topics

• CSCI 6680 - Computer Vision
• DSCI 6006 - Leadership and Entrepreneurism
• DSCI 6015 - AI and Cybersecurity
• DSCI 6653 - Bayesian Data Analysis
• Any new courses introduced by the program as special topics with course numbers within the range of DSCI 6670 and 6679.

Electives

Students taking one Special Topics course must select an elective and vice versa.

• BANL 6310 - Data Visualization and Communication
• BANL 6600 - Power BI and Dashboarding
• CMBI 6620 - Bioinformatics
• CSCI 6624 - Advanced Database Systems
• CSCI 6627 - Distributed Database Systems
• CSCI 6634 - Cryptography and Data Security
• CSCI 6638 - Small-Scale Digital Forensic Science
• CSCI 6646 - Introduction to Computer Security
• ECON 6635 - Business Forecasting
• EGRM 6611 - Decision Making Under Uncertainty
• INDE 6620 - Optimization and Applications
• INDE 6645 - Data Analytics
• INDE 6647 - Supply Chain Analytics and Resilience
• PUBH 6680 - Health Analytics

Required Courses (3 credits) - may be waived

Students without sufficient skills in programming will be required to take the following course:

• DSCI 6602 - Introduction to Programming for Data Science

Course Plan

A sample course plan (30 credit hours) for students exempted from taking the

DSCI 6602 - Introduction to Programming for Data Science course:

A sample course plan (33 credit hours) for students required to take DSCI 6602 -

Introduction to Programming for Data Science: