Master of Science In Data Science

Data Science is one of the hottest new fields in technology, driving innovation both at technology leaders such as Google and Facebook, as well as in established markets such as security, healthcare, and energy. Data scientist is one of the hottest new jobs of the last decade, with high demand, high salaries, and high marks for job satisfaction.

Please note: This program is no longer accepting applications. We encourage you to check out our Master of Science in Artificial Intelligence.

Learn to Extract Insights from Data

Data Science is an emerging field that combines methods from machine learning, artificial intelligence, and statistics with entirely new technologies for handling vast amounts of complex and quickly-changing data. The job of a data scientist is to apply these methods to gather information and achieve goals that are otherwise impossible for human experts due the large quantities and complexity of the data.

In the University of New Haven’s M.S. in data science program, you will develop proficiencies in the key skills expected of leading data scientists, including deep learning and statistical analysis, and the data skills needed to work with unstructured data and Natural Language Processing (NLP).

Selected Courses and Programs

  • An introduction to machine learning theory, design and implementation. Includes mathematical fundamentals, methods for classification, regression, unsupervised learning, and core concepts from statistical learning theory. Course will emphasize and use Python tools and machine learning application to real datasets.

  • An introduction to the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision theoretic modeling paradigm.

  • This course covers artificial neural networks and modern network architectures with an overview of achievements and open problems in deep learning. Emphasis is placed on hands-on programming using modern frameworks and real data. Topics include convolutional, recurrent, and unsupervised-learning networks.

  • An exploration for essential data science skills involved in working with unstructured data, including transforming it into structured data types able to be analyzed, processed, and used for machine learning and information retrieval algorithms. Material focuses on natural language processing and classification techniques used in text mining.  

  • Advanced topics in "Big Data" infrastructure and architectures focusing on computing resources and programming environments to support the development of efficiently scalable high-volume distributed machine learning algorithms.  

  • The University of New Haven offers a wide variety of in-depth courses that create a transformational educational experience for our students. To view the complete list of courses you'll take while pursuing a M.S. in Data Science, check out the Academic Catalog:

    Data Science, M.S.