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Dec 03, 2024
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2024-2025 Graduate Catalog
Data Science, M.S.
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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:
- Perform explorative data analysis in the context of real world applications.
- Design and build appropriate algorithms to model and interpret data.
- Build an end-to-end distributed data-pipeline.
- Apply subject-matter expertise to the design and development of data-driven solutions.
- Demonstrate the ability to work independently.
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Required Courses (21 credits)
Internship or Capstone (3 credits)
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.
Electives
Students taking one Special Topics course must select an elective and vice versa.
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
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DSCI 6001 - Math for Data Scientists
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DSCI 6002 - Intro to Data Science
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DSCI 6612 - Intro to Artificial Intelligence
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Second Semester
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DSCI 6003 - Machine Learning
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DSCI 6007 - Distributed & Scalable Data Engineering
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Elective/Special Topic Course
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Third Semester
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DSCI 6004 - Natural Language Processing
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DSCI 6011 - Deep Learning
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Elective/Special Topic Course
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Fourth Semester
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DSCI 6010 - Data Science Internship or Capstone Project
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A recommended course plan (33 credit hours) for students who are required to take DSCI 6602 -
Introduction to Programming for Data Science:
First Semester
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DSCI 6602 - Introduction to Programming for Data Science
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DSCI 6001 - Math for Data Scientists
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DSCI 6002 - Intro to Data Science
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Second Semester
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DSCI 6003 - Machine Learning
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DSCI 6612 - Intro to Artificial Intelligence
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DSCI 6007 - Distributed & Scalable Data Engineering
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Third Semester
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DSCI 6004 - Natural Language Processing
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DSCI 6011 - Deep Learning
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Elective/Special Topic Course
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Fourth Semester
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DSCI 6010 - Data Science Internship or Capstone Project
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Elective/Special Topic Course
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