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The University of Texas at ArlingtonThe University of Texas at Arlington

College of Science

Data Science Program

Courses

The College of Science plans to offer a new Bachelor’s degree program in Data Science. The program will include the following courses. Please watch the Schedule of Classes to see when they are offered.

DATA 1301: Introduction to Data Science
A survey of contemporary approaches to data-driven discovery. This course will be the required entry point for students majoring in Data Science, and will be designed to be accessible to all others interested in the modern data revolution. The course will include discussions of ethical principles involving privacy, data security, and broader societal implications. It will be proposed to be included as a Science option in the Core Curriculum. 

DATA 1401: Introduction to Scientific Computing 1
DATA 1402: Introduction to Scientific Computing 2
These two courses will provide the necessary foundations in scientific computing for Data Science majors, building from the basic computer competency core course (CSE 1310, 1312, or equivalent). They will introduce a number of operating systems, languages, and tools using examples and contexts from natural and behavioral sciences, such as Unix, Python, R, Sparc, Hadoop, SQL, databases, the cloud, visualization, scripting, github, and portfolio creation.

The following courses will be offered in future semesters.

DATA 3401: Data Mining, Management, and Curation
This lecture and lab course will provide training in working with databases, including data mining techniques and principles and best practices in data management, storage, and curation.

DATA 3402: Statistical Modeling and SAS
This lecture and lab course will provide training in statistical analysis and modeling, through techniques such as linear and generalized linear models, Bayesian modeling and information theory, and will develop proficiency in use of the SAS platform.

DATA 3403: Simulation and R
This lecture and lab course will provide training in techniques such as randomization, bootstrapping, and stochastic simulation, and will develop proficiency in the use of the R language.

DATA 3404: Machine Learning
This lecture and lab course will provide training in techniques of machine learning such as random forests, and support vector machines. Applications to big data will be emphasized.

DATA 4301: Data Problems
This course is intended for Junior-level Data Science students, and will enable them to identify, define, and explore a number of potential problems and projects, for follow-up in the capstone course sequence.

DATA 4302: Data Capstone Project 1
DATA 4303: Data Capstone Project 2
This two-semester sequence will involve deep engagement in a team or individual project in Data Science. Presentation of written and oral reports will be required in the second semester.