Academic Catalog 2025–2026

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Master of Science in Data Science (online)

Mission

The mission of the Online MS in Data Science program is to provide students with the ability to integrate the theory and practice of computing in the representation, processing, and use of information while upholding the tradition of the liberal arts education.

Program Educational Objectives

Graduates of the Online MS in Data Science Program shall:

  1. Effectively tackle complex real-world problems in various domains, applying advanced knowledge and skills in data science, including data analysis, machine learning, artificial intelligence, statistics and programming.
  2. Engage in continuous learning and professional development activities to stay abreast of the latest advancements in data science and the computing field.

Student Outcomes

Upon graduation, students will be able to:

  1. Analyze a complex problem and apply principles of computing and other relevant disciplines to elaborate solutions.
  2. Design, implement, and evaluate a computing-based solution to meet a given set of requirements in the context of data science.
  3. Communicate effectively in a variety of professional contexts.
  4. Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
  5. Function effectively as a member and leader of a team engaged in activities appropriate to the data science discipline.
  6. Apply theory, techniques and tools throughout the data science lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.

Admission Requirements

Online Application Form Apply Now
Degree Bachelor’s degree from a recognized university.
Minimum GPA 2.5 minimum GPA on a 4.0 scale.
Transcripts Official copies of all undergraduate and graduate college transcripts.
Work Experience Recommended, but not required. Computing experience is not necessary.
Other Requirements CV or resume.
Start Dates January, March, June, September and October.
English Language Proficiency Applicants from programs where English is not the language of instruction must submit proof of proficiency by passing either IELTS, TOEFL iBT, or Duolingo English Test with the minimum scores respectively of 6.5, 80, and 115.

 

 

 

 

 

 

 

 

 

 

Curriculum

A total of 30 credits are required as follows:

  • Core Requirements (15 credits)
  • Elective Courses (15 credits)

Core Requirements (15 credits)

  • DSC602 Python for Data Science (3 cr.)
  • DSC604 Statistics for Data Science (2 cr.)
  • DSC610 Data Science and Its Applications (3 cr.)
  • DSC611 Applied Machine Learning (3 cr.)
  • DSC612 Data Ethics (1 cr.)
  • DSC698 Data Science Project (3 cr.)

Elective Courses (15 credits)

  • DSC603  R Programming (1 cr.)
  • DSC605  Time Series Analysis (1 cr.)
  • DSC613  Data Engineering (1 cr.)
  • DSC614  Data Visualization (2 cr.)
  • DSC615  Big Data Analytics (2 cr.)
  • DSC622 Deep Learning and its Applications (3 cr.)
  • DSC623 Natural Language Processing with Deep Learning (2 cr.)
  • DSC624  Reinforcement Learning (2 cr.)
  • DSC625  Introduction to Generative AI (2 cr.)
  • DSC626  Recommender Systems (1 cr.)
  • DSC641  Business Analytics for Competitive Advantage (3 cr.)
  • DSC642  Analytics Applications (3 cr.)
  • DSC643  Statistical Methods in Finance (3 cr.)
  • DSC652  Artificial Intelligence for Managers    (3 cr.)
  • DSC653 Bridging Search and Generation in AI with RAG (1 cr.)
  • DSC660O Artificial Intelligence: Principles and Techniques (3 cr.)