Data Science and Artificial Intelligence, M.S.
Master of Science
About this program
The Master of Science in Data Science and Artificial Intelligence helps you build deep knowledge in computer science, statistics, AI and machine learning. You gain skills in building software systems and tackling real-world data problems — whether you come from a computing background or not. You finish your degree with an applied research project or thesis, supervised by faculty, to create a meaningful software solution and add a standout piece to your portfolio.
Program Curriculum and Requirements
Program Scope
The Master of Science in Data Science and Artificial Intelligence (DS&AI) program prepares students for high-demand industry positions in DS&AI and for doctoral programs that require a solid knowledge base in computer science, statistics, machine learning, and artificial intelligence. The program combines a broad and in-depth core curriculum in theory and applications. Students will receive rigorous and hands-on training through high-quality research activities to gain software system-building experiences in interdisciplinary settings. Through this program students with and without a Computer Science background will advance their careers by acquiring computational, statistical and system-building skills in this increasingly data-driven society.
Program Learning Outcomes
- Design and develop software systems to tackle problems throughout the life cycle of data science and Artificial Intelligence. Major components in this life cycle include: data collection/acquisition, data storage/management, data preprocessing, data modeling and machine learning, and visualization.
- Obtain an in-depth understanding of a host of machine learning/data mining algorithms; apply, implement, and evaluate such algorithms to extract knowledge from both structured and unstructured data.
- Utilize distributed and parallel computing platforms that are capable of managing and processing big data using computing facilities on premise or in the cloud.
- Analyze potentially unethical practices in data science and AI and adopt best practices to become a socially and ethically responsible professional.
- Communicate the data systems effectively with multidisciplinary audiences using verbal, written, and visual forms.
Admissions Information
In addition to the general requirements for admission, successful applicants to this program must:
- Hold a baccalaureate degree from a regionally accredited 4-year institution or shall have completed equivalent academic preparation as determined by the appropriate campus authority in a quantitative/computing field, including but not limited to computer science, mathematics, physics, statistics, engineering or relevant fields. Applicants are expected to demonstrate knowledge by having satisfactorily completed courses or worked in the information technology industry in the following areas: data structures, programming, analysis of algorithms, database systems, software engineering, calculus, probability, and/or statistics. However, an applicant who is deficient in these areas may be admitted conditionally on passing a set of undergraduate courses during the first calendar year of study.
- Have a 3.0 GPA or higher in their earned undergraduate degree or have earned a post-baccalaureate degree.
- Submit a general GRE score that has been taken within the last 3 years.
- Submit a TOEFL score (minimum 550/80) or IELTS score (minimum 7.0) obtained within the past two years if their undergraduate degree is from a country where the official language is not English.
- Two letters of recommendation
- Submit a Statement of Purpose
- Submit a CV or resume
Fall: March 1
Spring: October 1
Ready to apply? Visit the Graduate Students page to get started.
We’re Here to Help
Questions about the program or how to apply? Don’t hesitate to reach out.
Timothy Sun
- Assistant Professor
- Graduate Coordinator
- Graduate Advisor