Feb 25, 2024  
2023-2024 Graduate Bulletin 
    
2023-2024 Graduate Bulletin

Computer Science and Quantitative Methods (M.S.)


 

Dr. Jiang Li 
Department of Computer Science and Information Technology
Professor
Program Coordinator: Computer Science and Quantitative Methods Data Management and Analysis Concentration
Location:  Maynard Mathematics and Computer Science Building, Room 211
Phone: 931-221-7828
Email: gradpsm@apsu.edu
Website: www.apsu.edu/csci


Dr. Joseph Elarde
Department of Computer Science and Information Technology
Associate Professor
Program Coordinator: Computer Science and Quantiative Methods Information Assurance and Security Concentration
Location:  Maynard Mathematics and Computer Science Building, Room 227
Phone: 931-221-7301
Email: elardej@apsu.edu
Website: www.apsu.edu/csci

 

Dr. Ramanjit Sahi
Department of Mathematics and Statistics
Professor
Program Coordinator: Computer Science and Quantiative Methods Mathematical Finance Concentration
Location:  Maynard Mathematics and Computer Science Building, Room 231
Phone: 931-221-7812
Email: sahir@apsu.edu
Website:  www.apsu.edu/mathematics

 

Dr. Jackie Vogel
Chair, Department of Mathematics and Statistics
Professor
Program Coordinator: Computer Science and Quantiative Methods Math Instruction Concentration
Location:  Maynard Mathematics and Computer Science Building, Room 204
Phone: 931-221-7313
Email: vogelj@apsu.edu
Website:  www.apsu.edu/mathematics

 

Dr. Matt Jones
Department of Mathematics and Statistics
Professor
Program Coordinator: Computer Science and Quantiative Methods Predictive Analytics Concentration
Location:  Maynard Mathematics and Computer Science Building, Room 236
Phone: 931-221-7814
Email: jonesmatt@apsu.edu
Website:  www.apsu.edu/mathematics

 

 

The Department of Computer Science and Information Technology and the Department of Mathematics and Statistics at Austin Peay offer both an online and on-campus Master of Science degree ideal for professionals in a wide variety of science and math career fields.

The Master of Science (M.S.) in Computer Science and Quantitative Methods bring together science and business skills to give students a greater competitive advantage in the workforce. Both degrees enable students to pursue advanced training while working fulltime. The concentrations listed below are ideal for anyone with a bachelor’s degree, working in industry or military, and/or having a desire to advance their career with a technical degree. These programs are designed to allow students to complete their degrees while continuing to hold employment.

The M.S. program offers five concentrations:

  1. Data Management and Analysis (online and on-campus)
  2. Predictive Analytics (online and on-campus)
  3. Information Assurance and Security (online and on-campus)
  4. Mathematical Finance (online and on-campus)
  5. Mathematics Instruction (online and on-campus)

The programs are offered online, hybrid, and on-campus through the APSU Clarksville Campus and the Fort Campbell Campus allowing for students to gain admission for all terms.

Listed below are the required application materials and the associated scores (if necessary) for each.

Admissions Requirements

  • Application for admission
  • Application Fee:  $45 domestic or $55 international
  • Official transcripts from all colleges attended
  • Verification of lawful presence in the United States (i.e. submit a license or other approved document)
  • Bachelor’s degree, conferred in any field, from accredited institutions indicating a cumulative undergraduate GPA of at least 2.5
  • GRE scores are not required (optional)
  • Resume listing three references
  • Personal Essay (the Personal Essay should be no longer than one page and should address the applicant’s career goals, why the applicant wishes to pursue the MS at APSU, and the applicant’s quantitative/analytical background in terms of prior coursework, research, and/or employment)
  • Military documents (if applicable)
  • Admission decision by department

Admission decisions will be based largely on coursework and performance in all previous degree programs, GRE scores (optional), and the personal essay. The academic transcript, scores, and/or work experience of successful applicants must include evidence of aptitude, knowledge, and skill in algebra, quantitative literacy, and foundations of computer programming. Some background in statistics or calculus is desirable and will strengthen an application, as will additional experience in computer programming. Only completed application packets will be forwarded to the committee for review.

For more information about the application process, please visit apsu.edu/grad-studies.