Program type:


On Campus
Est. time to complete:

2-3 semesters
Credit Hours:

Discover the latest techniques and use technology to manage data for research and solve complex problems in your area of expertise.
The Computational Science certificate provides students a broad knowledge base in problem-solving using contemporary computational methods and tools, as well as specialized experience in modeling and solving complex problems in a particular focus area. Computational and data-intensive methods have become an essential aspect of all scientific disciplines. This certificate provides students with competitive skills whether they intend to pursue graduate education or a career in the industry.

Want more info?

We're so glad you're interested in UNT! Let us know if you'd like more information and we'll get you everything you need.

Request More Info

Why Earn a Computational Science Certificate?

The University of North Texas offers upper-division undergraduate academic certificates to meet workforce needs or to provide students with life/career skills and knowledge and to allow for specialization in academic disciplines.

The computational science certificate will teach you the technology and programming solutions to solve problems in your focus area. Students can specialize in math, physics, biology, or chemistry and graduate career-ready with an in-demand skill set.

Computational Science Certificate Courses You Could Take

Data Analytics and Computational Statistics 1 (3 hrs)
Provides an overview of quantitative methods essential for analyzing data, with an emphasis on science and industry applications. Topics include identification of appropriate metrics and measurement methods, descriptive and inferential statistics, experimental design, parametric and non-parametric tests, simulation, and linear and logistic regression, categorical data analysis, and select unsupervised learning techniques.
Principles of Data Visualization for Large Data (3 hrs)
Principles and methods for effective visualization and communication of large data sets. Standard and open source data visualization packages are used to develop presentations that convey findings, answer science and industry questions, drive decisions, and provide persuasive evidence supported by data.
Fourier Analysis (3 hrs)
Application-oriented introduction to Fourier analysis, including Fourier series, Fourier transforms, discrete Fourier transforms, wavelets, orthogonal polynomials and the Fast Fourier Transform (FFT) algorithm. The theoretical portions of the course emphasize interconnections and operator algebraic formalism.
Introduction to Computational Chemistry (3 hrs)
Introduction to the use of modern computational methodologies for the study of physical properties and chemical reactions of importance in chemistry, biochemistry, molecular biology and environmental sciences.
Biocomputing (3 hrs)
Introduction to computational problems inspired by the life sciences and overview of available tools. Methods to compute sequence alignments, regulatory motifs, phylogenetic trees and restriction maps.
Physics, Computation and Software Applications (3 hrs)
A basic survey of selected topics at the intersection of computer science, engineering and physics. Student will learn computer programming for applications in physics as well as the physics underlying computation and its physical implementation. Topics include automated control in experimental physics, symbolic computation/analysis, simulation of physical phenomena; physical basis of contemporary computers and computation; physical constraints with respect to size, speed, energy and architecture; classical and quantum computation and implementations.

Learn More About UNT

Watch this video to learn more about what makes UNT great!