The Master of Science in data science prepares students for positions in the exploding new fields of data analytics, big data, and data science. The program combines fundamental study in the mathematical foundations with hands-on training in key programming and data analysis tools.
Data scientist has been named the best job in America for the last three years by glassdoor.com with high scores for salaries and job satisfaction. Data science application areas are the core technologies of several of the largest corporations in the world, as well as the most exciting startups of today.
The US Bureau of Labor Statistics (BLS) estimates those in the role of “Computer and Information Research Scientists” with a Master’s degree, earned median pay of $114,520/year (2017). The BLS projects the role to grow much faster than average over the next ten years (19%).
Selected Application areas
- Recommendation systems
- Business intelligence
- Marketing
- Finance
- Healthcare
Hands-on Application
The experiential education focus of the University of New Haven emphasizes project-based learning with cutting-edge tools and data. Graduates will be well-prepared to work in an enterprise setting, a fast-moving entrepreneurial environment, or to proceed into the research domain.
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Background Required
The program does not presuppose a strong mathematical background, though previous coursework in linear algebra, probability and statistics will be helpful for certain methods and application areas. A review of the necessary mathematical background will be provided. Programming skills will be heavily emphasized and developed. Applicants lacking the basic requirements can opt to start early to fill prerequisites.
Curriculum
30 graduate credits are required for completion.
- Two courses (6 credits) in mathematical and statistical fundamentals for data science
- Four courses (12 credits) in machine learning and artificial intelligence, including both required and optional courses on statistical learning and deep learning methods.
- One course (3 credits) in entrepreneurship and leadership.
- One course (3 credits) in scalable and parallel computing methods
- One course (3 credits) in special topics in data science applications, including possible options in health sciences, business, finance, and other areas.
- Capstone project or internship (3 credits)
Required Courses
- DSCI 6001 Math for Data Scientists
- DSCI 6002 Data Exploration
- DSCI 6003 Machine Learning & Data Analysis I
- DSCI 6004 Unstructured Data/Natural Lang Proc
- DSCI 6005 Machine Learning & Data Analysis II
- DSCI 6006 Leadership and Entrepreneuism
- DSCI 6007 Distributed & Scalable Data Eng
- DSCI 6008 Special Topics
- DSCI 6010 Artificial Intelligence
- DSCI 6051 Data Science Internship or Capstone Project
Course Length
- A full-time student is expected to take three courses per semester and finish within 1.5 to 2 years.
- A part-time student can complete the course within 3 to 4 years, with many offered in the evenings.
Scholarships
We offer two types of scholarships/assistantship to our international master’s students.
Dean’s scholarship provides up to 50% tuition assistance during their enrollment.
Provost Assistantship offers 75% tuition assistance and the opportunity to work for an academic department up to 20 hours per week during their enrollment.