M.S. in Analytics and Modeling

Analytics and modeling focuses on the integration of knowledge and methodologies from mathematics, statistics, and computer science to analyze and solve problems in science, engineering, and other fields. As scientific and engineering fields deal with increasingly complex and expanded information and data sets, the need for individuals with such computational skills is expected to expand greatly. This 36-credit program provides students with a set of highly marketable skills applicable to many areas of science, industry, business, and government.


  • Core courses built around statistics, databases, and visual imaging
  • Advanced coursework in computational applications, including modeling techniques
  • Experience in a data-focused programming language, such as Python, R, or SAS
  • Research projects and internships allowing students to apply their skills to real-world problems
  • A 4+1 B.S./M.S. Early Entry program allows qualified undergraduate students at Valpo to complete the M.S. in Analytics and Modeling in one year

Students complete five required core courses built around statistics, databases, and visual imaging and take at least one course in computational applications in science, engineering, or other applied areas. Students also complete either an internship experience or a research project. To allow specialization, students fill out the program with elective coursework in computational science applications, mathematics, or computer science.

Core Requirements (15 credits)
AMOD 533 Data Mining 3 Credits
CS 525 Simulation and Modeling 3 Credits
IT 600 Ethics in Information Technology 3 Credits
IT 603 Information Management 3 Credits
ECON 525 (OR)

STAT 540

Applied Econometrics (OR)

Statistics for Decision-Making

3 Credits
Core Applications in Computational Science (3 credits)
At least one course from the following options:
AMOD 560 Computational Molecular Science 3 Credits
AMOD 610 Business Analytics 3 Credits
AMOD 620 Bioinformatics 3 Credits
AMOD 640 Topics in Biostatistics 3 Credits
AMOD 650 Computational Social Science 3 Credits
ECON 573 Applied Data Science 3 Credits
MATH 521 Mathematical Models of Infectious Disease 3 Credits
MET 530 Numerical Weather Prediction 3 Credits
Capstone Experience (3-6 Credits)
AMOD 686 Internship 1-3 Credits
AMOD 792 Research Project 1-3 Credits
AMOD 798 (AND)

AMOD 799

Thesis Proposal (AND)


6 Credits
Electives (15 credits may be selected from Core Applications or from the following options)
AMOD 545 Evolutionary Algorithms 3 Credits
AMOD 550 Scientific Visualization 3 Credits
AMOD 565 Interactive Computer Graphics 3 Credits
AMOD 574 Computational Linear Algebra 3 Credits
AMOD 590 Topics in Analytics and Modeling 1-3 Credits
AMOD 690 Advanced Topics in Analytics and Modeling 1-3 Credits
AMOD 695 Independent Study 1-3 Credits
CS 572 Computability and Computational Complexity 4 Credits
GEO 515 Advanced Geographic Information Systems (GIS) 3 Credits
IT 664 Natural Language Technologies 2 Credits
MATH 520 Dynamical Systems 3 Credits
MATH 522 Optimization 3 Credits
MATH 523 Game Theory 3 Credits
MATH 530 Partial Differential Equations 3 Credits
MATH 570 Numerical Analysis 3 Credits
MATH 571 Experimental Mathematics 3 Credits
STAT 541 Probability 4 Credits
STAT 543 Time Series Analysis 3 Credits
STAT 544 Stochastic Processes 3 Credits
STAT 561 Introduction to R 1 Credit
STAT 563 Introduction to SAS 3 Credits
STAT 590 Advanced Topics in Statistics 1-3 Credits

Undergraduate students at Valparaiso University may complete the M.S. in Analytics and Modeling in one year by following a special track that ensures completion of all admission requirements and allows elective graduate coursework during their senior year. As part of their undergraduate study, such students should have completed the following courses with a grade of B or higher by the end of their junior year:

  • MATH 131 Calculus I (4 credits)
  • MATH 264 Linear Algebra (3 credits) or MATH 260 Linear Systems and Matrices (1 credit)
  • STAT 240 Statistical Analysis (3 credits), or a similar introductory statistics course
  • CS 157 Algorithms and Programming (3 credits)

Students are also encouraged to take MATH 132 Calculus II (4 credits) and CS 158 Algorithms and Abstract Data Types (3 credits).

Students must also have at least a 3.0 cumulative GPA. Students interested in pursuing this track should consult with the Graduate School and/or the Analytics and Modeling program director, Tiffany Kolba, during their junior year.