Online Master of Science in Data Science
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:
- 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.
- 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:
- Analyze a complex problem and apply principles of computing and other relevant disciplines to elaborate solutions.
- Design, implement, and evaluate a computing-based solution to meet a given set of requirements in the context of data science.
- Communicate effectively in a variety of professional contexts.
- Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
- Function effectively as a member and leader of a team engaged in activities appropriate to the data science discipline.
- 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 (deadline: January 10, 2024 - start date: January 20, 2025) |
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)
- AAI602 Python for Data Science (3 cr.)
- AAI611 Applied Machine Learning (3 cr.)
- AAI614 Fundamentals of Data Science (3 cr.)
- AAI615 Data Ethics (1 cr.)
- DSC604 Statistics for Data Science (2 cr.)
- DSC698 Data Science Project (3 cr.)
Elective Courses (15 credits)
- AAI612 Deep Learning and its Applications (3 cr.)
- AAI630 Data Visualization (2 cr.)
- AAI634O Data Engineering (1 cr.)
- AAI651 Natural Language Processing with Deep Learning (2 cr.)
- CSC611 Design and Analysis of Algorithms (3 cr.)
- CSC660 Artificial Intelligence: Principles and Techniques (3 cr.)
- DSC603 R Programming (1 cr.)
- DSC605 Time Series Analysis (1 cr.)
- DSC615 Big Data Analytics (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 (2 cr.)