Nov 03, 2024  
2024-2025 Graduate Catalog 
    
2024-2025 Graduate Catalog

Data Science and Artificial Intelligence, MS (53-1006) (30 hours) [Also available as an accelerated program]


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The Master of Science in Data Science and Artificial Intelligence degree is designed to prepare graduates with advanced skills in Data Science and Artificial Intelligence. The graduates from the program can apply these skills to identify, collect, analyze, manage and transform complex data sets to make informed decisions. Besides acquiring experience in top programming languages, you will also gain hands-on practice with leading data analytics software and platforms.

Student Learning Outcomes - The graduate with a Master of Science degree in Data Science and Artificial Intelligence will use the knowledge and skills obtained in the program to:

  • Demonstrate proficiency in applying mathematical and statistical principles to data science and artificial intelligence applications.
  • Demonstrate an ability to obtain, clean, process and transform large data sets with professional software, packages, and tools to create solutions for real-world applications and help businesses and organizations make informed decisions.
  • Apply analytics and artificial intelligence techniques to satisfy the business needs of a wide range of stakeholders.
  • Communicate effectively with a range of audiences, work effectively in a team environment, and demonstrate an understanding of ethical concerns related to data science and artificial intelligence.

Admission Requirements - Admission is granted on the basis of applicant’s aptitude and potential which will be evaluated through academic records, test scores and/or work experience. To be admitted to the program, a student must have a minimum undergraduate grade point average (GPA) of 2.8. Candidates must complete the Graduate Record Examination (GRE) with a minimum combined score of 291 in Verbal and Quantitative reasoning Applicants must submit official GRE test scores by Educational Testing Services (ETS) directly to the University of Central Missouri. The ETS institution code for sending GRE scores to UCM is 6090, program code is 0402. Applicants with exceptional undergraduate performance may be considered with a lower GRE score. The GRE test requirement can be waived if any one of the following conditions is satisfied.

  • The student is a graduate of a regionally accredited college or university with a degree in Computer Science/Data Science/Engineering/Information Technology/Information Systems/Mathematics/Statistics and a GPA of 3.25 or more. Students not in the above mentioned discipline list should have a GPA of 3.5 or more.
  • The student has earned an M.S. or more advanced degree in a closely related discipline.
  • The student has a minimum 3 years of relevant work experience in a US based corporation or a reputed multinational organization.

International students whose native language is not English and do not have a US degree are required to take the Test of English as a Foreign Language (TOEFL). A minimum TOEFL score of 79 is required. Dualingo and IELTS scores are also accepted at UCM. Regular graduate students should have a composite exam score of 120 in Duolingo or a band score of 6.0 in IELTS. The English requirement is waived for applicants who have completed a minimum of 60 semester credit hours or have earned a bachelor or graduate degree from an accredited college or university in the USA. Submission of a statement of purpose and three letters of recommendation is OPTIONAL for admission. They may however be required if the student applies for graduate assistantship or student worker positions. Applicants who have degrees in some non-computing fields will also be considered for admission. Students may make up their deficiencies in data science by completing the required undergraduate background courses.

Full time students without deficiencies can expect to complete this program in two academic years.

Required Undergraduate Background Courses: 0-6 Semester Hours


The following undergraduate courses (or equivalent) are required for students who did not have python programming and data analytics in their undergraduate study.

  • CS 2030 -  Python Programming II (3)
  • DSA 1000 -  Introduction to Data Analytics (3)

Select 1 of the 2 Areas: 18 Semester Hours


Area 1 - Data Science: 18 Semester Hours


Area 2 - Artificial Intelligence: 18 Semester Hours


Minimum Graduate Hours Total: 30 Semester Hours


  • Only up to 3 credit hours of DSA 5020 - Internship in Data Science and Artificial Intelligence (3)  can be applied to a student’s degree program. Students are expected to take DSA 5020  . If the student is unable to secure an internship, any other graduate level CS/CYBR/DSA/SE course approved by the advisor, may be taken.
  • Students cannot take both CS 5040  and CS 6010 .
  • CS 6010  may only be used as a program elective for students completing a thesis. Students who complete this course and do not complete a thesis will be required to complete the additional required credit hours to meet the minimum hours requirements.

Accelerated Program Notes:


The Accelerated model for this program is designed for the BS Data Science.

UCM students having completed at least 9 hours of required courses in the BS Data Science curriculum above the 1000 level with a major GPA of at least 3.00 may consult with their faculty advisor and complete a school application to declare the accelerated BS/MS major in Data Science and Artificial Intelligence. Prior to beginning the graduate portion of the program, students in the accelerated program will need to apply to the UCM Graduate School for formal admission to the Accelerated BS/MS program.

Accelerated student may be eligible to include the following courses as overlap between the undergraduate and graduate programs. They would be taken at the Graduate level (5XXX):

CS 5160 - Advanced Applications Programming in Python (3)  (CS 4160)

CS 5200 - Database Theory and Applications (3)  (CS 4600)

CS 5220 - Advanced Applications Programming in Java (3)  (CS 4120)

CS 5610 - Introduction to Cloud Computing (3)  (CS 4610)

CS 5700 - Artificial Intelligence (3)  (CS 4700)

CS 5710 - Machine Learning (3)  (CS 4710)

CYBR 5240 - Web Application Security (3)  (CYBR 4140)

CYBR 5820 - Introduction to Information Assurance (3)  (CYBR 4820)

DSA 5100 - Programming Foundations for Data Science and AI (3)  (DSA 4100)

DSA 5200 - Advanced Data Visualization (3)  (DSA 4200)

DSA 5400 - Statistical Foundations for Data Science and AI (3)  (DSA 4400)

DSA 5600 - NoSQL Database Systems (3)  (DSA 4600)

DSA 5620 - Big Data Analytics (3)  (DSA 4620)

SE 5930 - Software Testing and Quality Assurance (3)  (SE 4930)

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