2022-2023 Graduate Catalog 
    
    Jan 31, 2023  
2022-2023 Graduate Catalog

Data Science, M.S.


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.  One of these courses (3 credits) is considered a prerequisite preparatory course, which may be waived by the program coordinator during the initial admission application review. Students will be informed if the course is waived or required at the time of admission. 

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.

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.

Required Courses (3 credits) - may be waived


Students without sufficient skills in Python programming will be required to take the following course. This determination is made during the admissions process, and students will be informed at the time of admission if this course is required or waived. Students who choose to attend the university in this program agree to take the course if shown as required:

Course Plan


A recommended course plan (30 credit hours) for students who are NOT required to take 

DSCI 6602 - Introduction to Programming for Data Science:

First Semester

DSCI 6001 - Math for Data Scientists

DSCI 6002 - Intro to Data Science

DSCI 6612 - Intro to Artificial Intelligence

 

Second Semester

DSCI 6003 - Machine Learning

DSCI 6007 - Distributed & Scalable Data Engineering

Elective/Special Topic Course

 

Third Semester

DSCI 6004 - Natural Language Processing

DSCI 6011 - Deep Learning

Elective/Special Topic Course

 

Fourth Semester

DSCI 6010 - Data Science Internship or Capstone Project

 

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

Introduction to Programming for Data Science:

First Semester

DSCI 6602 - Introduction to Programming for Data Science

DSCI 6001 - Math for Data Scientists

DSCI 6002 - Intro to Data Science

 

Second Semester

DSCI 6003 - Machine Learning

DSCI 6612 - Intro to Artificial Intelligence

DSCI 6007 - Distributed & Scalable Data Engineering

 

Third Semester

DSCI 6004 - Natural Language Processing

DSCI 6011 - Deep Learning

Elective/Special Topic Course

 

Fourth Semester

DSCI 6010 - Data Science Internship or Capstone Project

Elective/Special Topic Course