Dean's Office: Life Sciences Building, Room 206

Office hours: Mon-Thu 10 a.m. to 2 p.m

501 S. Nedderman Drive, Arlington, TX 76019

Phone: 817-272-3491

Fax: 817-272-3511

Email: cos@uta.edu

Level up with a unique ** Data Science bachelor's degree from the College of Science at UTA**. Maverick Scientists are becoming better data scientists and sharpening their ability to do better science by earning a data science degree with an emphasis in their specific field of science. Discover important data relationships, learn to sort through large data sets and extract meaningful insights using industry standard tools and best practices, leveraging data to answer difficult questions and tackle real world challenges, directly in their scientific area of interest or across multiple disciplines.

Data Science

UTA’s Data Science program aims to train Maverick Scientists who can solve any analytical problem, regardless of the field. You’ll learn the software and skills necessary today, but also the foundations to grow and evolve in the quickly changing industry. UTA Data Scientists will be empowered to do better research and become better scientists in their chosen area of interest.

Since 2016, Glassdoor report ranks Data Scientist as the best job in the US. This report ranks jobs according to each job’s Glassdoor Job Score, determined by combining three factors: number of job openings, salary, and overall job satisfaction rating. In addition to making you a better Maverick Scientist or raising your profile for graduate course work, a bachelors or minor in Data Science can help prepare you for a variety of Data related positions.

- Be a Better Scientist in your Chosen Field
- Data Scientist
- Machine Learning Engineer
- Machine Learning Scientist
- Applications Architect
- Enterprise Architect
- Data Architect
- Infrastructure Architect
- Data Engineer
- Business Intelligence (BI) Developer
- Statistician
- Data Analyst

UTA students currently have two flexible degree plan options – a bachelor's of science degree in Data Science with an emphasis in a science field (Biology, Chemistry, Environmental Science, Geology, Mathematics, Physics, and Psychology); or a minor in Data Science to pair with an existing major. Your course schedule may vary based on transferable credits or credits earned.

Students who wish to obtain a bachelor’s in Data Science must complete 120 hours, to include the following:

**46**UTA Core curriculum hours**23**hours in students scientific area of emphasis (Biology, Chemistry, Environmental Science, Geology, Mathematics, Physics, and Psychology)**8**hours of science elective with lab**18**hours of Data Science Foundations**16**hours of Data Science Core courses**9**hours of Data Science Capstone

**DATA Science Foundations:**

- UNIV-SC 1131 Student Success
- DATA 1301 Intro to Data Science
- DATA 3311 Mathematics for Data Science
- DATA 3401 Python for Data Science 1
- DATA 3402 Python for Data Science 2
- MATH 3316 Statistical Inference
- MATH 3313 Linear Algebra/Probability

**DATA Science Core:**

- DATA 3421 Data Mining, Management, and Curation
- DATA 3441 Statistical Methods for Data Science 1
- DATA 3442 Statistical Methods for Data Science 2
- DATA 3461 Machine Learning

**DATA Science Capstone**:

Additionally, students in the bachelor's program will complete a capstone project – an internship in industry or a research project in the university – which provides hands on work in a domain.

- DATA 4380 Data Problems
- DATA 4381 Data Capstone Project 1
- DATA 4382 Data Capstone Project 2

Students who wish to obtain a minor in Data Science must take at least 19-20 semester hours of DATA or related courses, to include the following:

**Foundational courses (take any four of these):**

- DATA 3311 Mathematics for Data Science
- DATA 3401 Intro to Scientific Computing 1
- DATA 3402 Intro to Scientific Computing 2
- DATA 3421 Data Mining, Management, and Curation
- DATA 3441 Statistical Methods for Data Science 1
- DATA 3442 Statistical Methods for Data Science 2
- DATA 3461 Machine Learning

*And any one of the following elective courses:*

- DATA 1301 Introduction to Data Science

*An additional DATA 34xx course listed in section 1*

- BIOL 3340 Bioinformatics
- ENVR / GEOL 4454 Statistics for Scientists and Engineers
- GEOL 4330 Understanding Geographical Information Systems
- MATH 3313 Intro to Probability
- MATH 3316 Statistical Inference
- PHYS 2321 Computational Physics
- PSYC 2443 Research Design and Statistics I

This course provides an introduction to the field of data science with a high-level overview of basic concepts, data types, and techniques while introducing data-informed decision making.

This course covers techniques from linear algebra and probability with an emphasis on how they are used in data science. Working with real data sets will be emphasized, along with basics of Matlab or R programming.

This is the first of a two-course sequence offering the foundations of Python programming in the context of data science. It introduces the full syntax of the Python language as it overviews structured, functional, and object-oriented programming methodologies. It also provides a basic conceptual understanding of computing and introduces Unix command-line tools, software employed in data science, such as git and Jupyter, and Python libraries such as numpy, matplotlib, and Pandas.

This is the second of a two-course sequence offering the foundations of Python programming in the context of data science. It reinforces concepts presented in DATA 3401 with greater depth and a focus on application to various problems in data science, while further exploring the python library ecosystem.

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. Prerequisite: DATA 3401, DATA 3402

This lecture and lab course will provide an introduction to the fundamental building blocks of advanced data analysis, with emphasis on advanced linear algebra, optimization, statistical inference, and Monte Carlo methods. Working with real data sets will be emphasized, along with basics of R programming.

This lecture and lab course will provide an introduction to the principles and general methods for the analysis of categorical data. This type of data occurs extensively in both observational and experimental studies, as well as industrial applications. While some theoretical statistical detail is given, the primary focus will be on methods of data analysis. Topics include generalized regression models, logistic regression models, Poisson regression models, and multinomial regression models. Problems will be motivated from a scientific perspective.

This course introduces and surveys Machine Learning techniques and their application to various problems in data science.

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.

This is the first of a two-semester sequence that will involve deep engagement in a team or individual project in Data Science. Presentation of written and oral reports will be required.

This is the second of a two-semester sequence that will involve deep engagement in a team or individual project in Data Science. Presentation of written and oral reports will be required.

"Students who graduate from this program will have developed strengths in data-driven problem solving and data visualization based on their ability to apply statistical and mathematical analysis using program-acquired database and programming skills. They will also have gained skills in the presentation of technical data in a form that non-technical management leaders can understand and implement. These skills are in high demand by employers."

- Dr. Minerva Cordero, College of Science Associate Dean

UTA provides need-based financial aid and scholarships to qualified individuals. Incoming domestic students are encouraged to fill out a FAFSA to determine need-based aid. A listing of current UTA scholarships is available in the Mav ScholarShop.

Scholarship recipients who are nonresidents of Texas or citizens of a country other than the United States of America may be eligible to pay the in-state tuition rate if they are offered a competitive scholarship through UTA. The competitive scholarships that may be considered for an out-of-state tuition waiver must be a minimum of $1,000 for the period of time within the academic year covered by the scholarship, not to exceed 12 months. *Please note that the out-of-state tuition waiver is not guaranteed, is contingent upon funding and may vary in availability.*

You’re off to a great start and chances are your academic progress will translate into progress towards a Data Science bachelor’s degree because of UTA’s intentional multidisciplinary approach. All Data Science majors take UTA’s core classes, plus course work in a scientific area of emphasis, and the required DATA classes as part of their degree plan. The bachelor’s program culminates with a capstone project – either an internship in industry or a research project in the university.

Because of the format of the Data Science program, there are many paths to fit a variety of needs, including Data Science with a minor in a scientific field, double majors or a traditional science major with a data science minor. You have the option to mix and match to get the data science knowledge and a degree that’s appropriate for you and your interests. Contact an advisor to see what your path to Data Science might look like.

Our program is committed to supporting multiple disciplines and being applicable in many areas of scientific research. Typical business school data science programs are more focused on specific skills and knowledge skills to inform decisions and solve problems in a corporate environment and are less focused on the science. UTA’s College of Science Data Science degree plans emphasize the scientific and theoretical aspects of data science, while also applying techniques for workplace integrations. Furthermore, UTA’s collaborative approach offers a chance for students and faculty from many different science disciplines to use data to tackle real world problems from a variety of angles and perspectives.

The field is growing and the list of companies with internship opportunities is ever changing, but past postings for the Dallas-Fort Worth area, or within a 50-mile radius of UTA’s campus, include Blackberry, Celanese, Ericsson, IBM, Mary Kay, PepsiCo, Sabre and others.

Absolutely. Since the fall of 2020, UTA has offered a Data Science minor. The program is designed to prepare students in various major degree programs to obtain skills and knowledge that have high value in the job market. Data scientist and similar job titles have consistently ranked highly in lists of “top 10 jobs” compiled by national news outlets in recent years. Advantages in the job market are especially likely when the Data Science minor is combined with strong quantitative preparation in the student’s major.

Yes! UTA has a variety of established and emerging degree programs related to Data Science to fit a number of student needs and career paths. In addition to the College of Science's bachelor's degree and minor in Data Science, the UTA College of Business offers a bachelor's and master's program in Business Analytics, UTA's Math Department has a PhD in Data Science, the Psychology Department as an emerging master's program in Learning Analytics and the College of Engineering has announced plans for a master's program in Data Science. Visit UTA.edu to browse course offerings and determine which program is right for you.

Better Data Scientists. Better Science. Build the skills to do better research by launching your career in Data Science.