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.
Highlights
- 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) |
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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 Analytics and Modeling (3 credits) |
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At least one course from the following options: | ||
ACRS 525 | Actuarial Modeling | 3 Credits |
AMOD 610 | Business Analytics | 3 Credits |
AMOD 620 | Bioinformatics | 3 Credits |
ECON 573 | Applied Data Science | 3 Credits |
GEO 515 | Advanced Geographic Information Systems (GIS) | 3 Credits |
GEO/MET 560 | Data Analysis | 3 Credits |
MATH 521 | Mathematical Models of Infectious Disease | 3 Credits |
MET 530 | Numerical Weather Prediction | 3 Credits |
Capstone Experience (3-6 Credits) |
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AMOD 686 | Internship | 1-3 Credits |
AMOD 792 | Research Project | 1-3 Credits |
AMOD 798 (AND)
AMOD 799 |
Thesis Proposal (AND)
Thesis |
6 Credits |
Electives (15 credits may be selected from Core Applications or from the following options) |
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AMOD 550 | Scientific Visualization | 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 545 | Artificial Intelligence | 3 Credits |
CS 565 | Interactive Computer Graphics | 3 Credits |
CS 572 | Computability and Computational Complexity | 4 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 542 | Mathematical Statistics | 3 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.
The certificate in Analytics and Modeling is intended for the working professional interested in a deeper knowledge of the statistical, computational, and mathematical methods behind modeling and data analytics. The certificate requires only 18 credits, rather than the 36 credits required for the M.S. in Analytics and Modeling.
Core Requirements (9 credits) |
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AMOD 533 | Data Mining | 3 Credits |
CS 525 | Simulation and Modeling | 3 Credits |
ECON 525 (OR)
STAT 540 |
Applied Econometrics (OR)
Statistics for Decision-Making |
3 Credits |
Applications in Analytics and Modeling (9 credits) |
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At least three courses from the following options: | ||
ECON 573 | Applied Data Science | 3 Credits |
IT 600 | Ethics in Information Technology | 3 Credits |
IT 603 | Information Management | 3 Credits |
MATH 521 | Mathematical Models of Infectious Disease | 3 Credits |
All students in Valpo’s M.S. in Analytics and Modeling program complete a 3-credit capstone experience, either an internship or research project, that provides students the opportunity to synthesize the skills they have learned in their coursework and apply them in a real-world setting. Below are examples of past capstone experiences completed by Analytics and Modeling students:
Internships
- Junior Data Scientist at Cherish Technologies, Spring 2022
- Big Data Analytics Intern at Graco Inc., Summer 2021
- Assessment and Analytics Intern at the University of North Carolina Pembroke, Spring 2021
- Transportation Planning and Analytics Intern at the Northwestern Indiana Regional Planning Commission, Fall 2020
Research Projects
- Analysis of Attendance Trends at the Valparaiso University Hesse Center, Mentor: Dr. Tiffany Kolba, Department of Mathematics and Statistics , Summer 2022
- Framework for Deep Reinforcement Learning Experimentation, Mentor: Dr. Michael Glass, Department of Computing and Information Sciences, Spring 2021
- Estimation of Population Parameters Using Sample Extremes from Nonconstant Sample Sizes, Mentor: Dr. Tiffany Kolba, Department of Mathematics and Statistics , Summer 2020
Courses are offered during three academic terms each year: Fall (August-December), Spring (January-May), and Summer (May-August). Students can enter the Analytics and Modeling program at the beginning of any of the three academic terms. Full-time students typically complete the M.S. in Analytics and Modeling program over three or four academic terms. Four academic terms is recommended for international students, who must also take GRD 500: Graduate Academic Success (0 credits) during their first term.
Example Three Term Degree Map:
Term 1 | Term 2 | Term 3 |
IT 600: Ethics in Information Technology | AMOD 533: Data Mining | Capstone Experience |
IT 603: Information Management | Elective | Elective |
STAT 540: Statistics for Decision Making | Elective | Elective |
CS 525: Simulation and Modeling | Elective | Elective |
Example Four Term Degree Map:
Term 1 | Term 2 | Term 3 | Term 4 |
IT 600: Ethics in Information Technology | CS 525: Simulation and Modeling | AMOD 533: Data Mining | Capstone Experience |
IT 603: Information Management | Elective | Elective | Elective |
STAT 540: Statistics for Decision Making | Elective | Elective | Elective |
Instructions for how to apply can be found on the Valpo Graduate School’s website.
If you are interested in learning more about our Master’s degree in Analytics and Modeling, please fill out and submit the form below and a graduate studies representative will respond to you soon.
What makes Valpo great is the commitment of the faculty and their desire to make you better both in the classroom and in the professional world. Valpo has an unbelievably advanced and sophisticated network of professors who teach the skills that are desired in today’s workforce. The small class sizes allowed for great conversations to occur during class and also allowed for direct access to professors.
–Ed Orlando ’16, Data Scientist