Computational and Data Science – Program of Study

Developing mathematical models, employing numerical methods and using data visualization has become increasingly important for a variety of business and industries. The Computational and Data Science Track incorporates coursework from different mathematical disciplines to reflect the breadth of computational and data science employed to solve real world problems.

The Computational and Data Science Track is offered through the College of Science.  There are two focus areas within the Track:

  • Applied Mathematics
  • Scientific Computing

Graduate Students in the Computational and Data Science Track take advanced science courses within these two focus areas and choose electives based on their professional goals. Core courses and electives total 18 credits. These areas of study include:

Applied Math

Statistics

Core courses:

MATH 5010 Probability
MATH 5080 Statistical Inference I
MATH 5090 Statistical Inference II

Electives:

MATH 5030 Actuarial Mathematics
MATH 5040 Stochastic Processes and Simulation I
MATH 5050 Stochastic Processes and Simulation II
MATH 5610 Introduction to Numerical Analysis I
MATH 5620 Introduction to Numerical Analysis II
MATH 5075 Time Series Analysis
MATH 6010 Linear Models
MATH 6020 Multilinear Models
MATH 6070 Mathematical Statistics

Applied Math

Core courses:

MATH 5610 Introduction to Numerical Analysis I
MATH 5620 Introduction to Numerical Analysis II
or
MATH 5710 Introduction to Applied Mathematics
MATH 5600 Survey of Numerical Analysis
or
MATH 6610 Analysis of Numerical Methods I
MATH 6620 Analysis of Numerical Methods II

Electives:

MATH 5440 Introduction to Partial Differential Equations
MATH 5410 Introduction to Ordinary Differential Equations
MATH 5470 Chaos and Nonlinear Systems
MATH 5500 Calculus of Variations with Applications
MATH 5750 Optimization
MATH 6790 Case Studies in CES

Computational Math, Biology

Core courses:

MATH 5010 Probability
MATH 5110 Mathematical Biology I
MATH 5120 Mathematical Biology II

Electives:

MATH 5470 Chaos and Nonlinear Systems
MATH 5040 Stochastic Processes and Simulation I
MATH 5050 Stochastic Processes and Simulation II
MATH 5080 Statistical Inference I
MATH 5090 Statistical Inference II
MATH 6770 Mathematical Biology I
MATH 6780 Mathematical Biology II

Financial Math

Core courses:

MATH 5010 Probability
MATH 5760 Introduction to Mathematical Finance I
MATH 5765 Introduction to Mathematical Finance II

Electives:

MATH 5030 Actuarial Mathematics
MATH 5040 Stochastic Processes and Simulation I
MATH 5050 Stochastic Processes and Simulation II
MATH 5075 Time Series Analysis
MATH 5080 Statistical Inference I
MATH 5090 Statistical Inference II
MATH 6010 Linear Models
ECON 5969 Special Topics in Economics

Scientific Computing

Core Courses:

CS 6210 Advanced Scientific Computing I
CS 6220 Advanced Scientific Computing II

Graphics and Visualization

Core Courses:

CS 5600 Introduction to Computer Graphics
CS 6600 Mathematical Foundations of Computer Graphics and Visualization

Electives:

CS 6610 Interactive Computer Graphics
CS 6630 Scientific Visualization
CS 6640 Introduction to Digital Image Processing
CS 6660 Physics-based Animation
CS 6665 Character Animation

Artificial Intelligence and Robotics

Core Courses:

CS 6300 Artificial Intelligence
CS 6310 Robotics

Electives:

CS 6320 Computer Vision
CS 6340 Natural Language Processing
CS 6350 Machine Learning
CS 6360 Virtual Reality

Advanced Quantitative Skills (6 credits)

MST 6600 Applied Statistical Techniques

AND one of the following five courses:

MATH 5010 Probability
MATH 5600 Survey of Numerical Analysis
MATH 5710 Introduction to Applied Mathematics
MATH 5740 Mathematical Modeling
CS 5010 Software Practice

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Transferable Skills (12 Credits)

MST 6010 Effective Communication (1)
MST 6012 Accounting and Finance (1)
MST 6020 Leadership and Management (1)
MST 6021 Strategic Planning and Marketing (1)
MST 6022 Production & Operations Management (1)
MST 6023 Entrepreneurship and New Product Development (1)

MST 6500 Scientific Reasoning (3)

electives: 3 credits of graduate coursework from the David Eccles School of Business or an approved elective (contact program director for a list of transferable skills electives)

Professional Experience Project (Internship; 3 Credits)

An essential component of the PMST degree is a Professional Experience Project (internship) working with a local company, government agency or non-profit organization. These activities engage students in real-world work situations involving technical problems, teamwork, communication skills, and decision-making.electives: 3 credits of graduate coursework from the David Eccles School of Business or an approved elective (contact program director for a list of transferable skills electives)

(Note: course availability is subject to change.)