The 10 Best Data Science Degree Programs in Texas

A&M-Victoria takes our top bachelor’s spot for value and access. Its 2026-27 resident base price is $4,383.54 for 15 hours. Extra fees may apply. That price is about 25% below UTA and UT Austin. It is 40% below UT Dallas’s incoming-resident variable-plan example. Aid and housing can change what a student pays.

The 36-hour Data Science concentration has 12 courses. Students take Python, database systems, data visualization, and analytics. Two statistics courses add the math. Privacy and ethics also appear in the required plan. Management and marketing put those tools in a business setting.

The school lists both Victoria and online study. Victoria College also publishes a direct AS-to-BS transfer map. That mix gives students more ways to keep housing and transfer costs down.

Faculty is another reason to look closely. Hardik Gohel teaches data science and AI. He won A&M-Victoria’s 2026 Faculty Award for Distinguished Teaching. He leads the Applied AI Research Lab. He also invites motivated college students to join his research team. Hongyu Guo leads the BS Computer Information Systems program. His work includes machine learning, AI, data mining, and big-data systems.

The degree is a BS in Computer Information Systems. Data Science is the concentration. The published plan names no required machine learning class, capstone, or internship. Ask how to add applied work before you enroll.

UTA requires 34 hours of data science foundations and core work. Students take Python, probability, data mining, statistics, and machine learning. They also pick a 23-hour science field. Choices include biology, chemistry, math, and physics. Environmental Science, geology, and psychology are also listed.

The nine-hour capstone is the strongest applied-work requirement in this group. A student can complete an industry internship or university research. The work spans three linked classes. It lasts longer than a one-term project.

Pick the science field with care. It shapes almost one-fifth of the degree. Labs can make the weekly load hard. The full program runs on campus. Ask an adviser to map the lab terms. Map the capstone terms too.

UT Dallas shares this degree across two schools. They are Mathematical Sciences and Computer Science. The 46-hour major core spans math and code. It covers data structures, databases, big data, and machine learning. Calculus, probability, and statistics carry equal weight.

A required four-credit capstone closes the degree. The 2026 catalog maps the early course order. It puts physics, calculus, and code before upper-level work. That sequence makes the transfer risk easy to spot.

Transfer students need the early math and CS core first. One missing course can block several later classes. Ask for a term-by-term map before you transfer. Then place those credits in the 120-hour plan.

UT Austin puts statistics first. The major core has seven courses. It covers probability, machine learning, and advanced methods. The case studies class uses those skills. Students solve one full data task.

The base is wider than those 22 major hours. Calculus, linear algebra, code, and databases are also required. A 12-hour breadth field adds another subject. The plan leaves 30 free-elective hours. That is room for a minor or more code.

The plan has no separate required capstone. UT admission does not promise this major. Check the major-entry rules first. Then add Austin housing to the posted tuition.

UNT’s Fall 2026 plan requires 12 courses. The core has four courses. It covers data science, mining, and machine learning. Math and statistics are also in the core. Guided choices reach deep learning and large data. Other choices cover text, software, and human-centered AI.

Students choose one of four final paths. They can do research, an internship, a capstone, or a thesis. That choice fits more types of students. It can serve a working analyst or a future PhD student. The last block takes 3 to 6 hours.

Choice still needs a plan. Tie each elective to a job skill. It should also feed the final project. DTSC 5503 is new for Fall 2026. Check when it will run again. This plan has 36 hours. The shorter public master’s plans here have 30.

Houston requires eight classes. They span statistics, models, and code. The plan also covers data visualization, big data, and deep learning. The 30-hour plan takes one year full time. A two-year part-time route is also available.

The final three credits come from MATH 6315. This Master’s Tutorial runs as an internship. That work is required. Several other plans make the final project optional.

The degree is based on campus. Some classes have hybrid or live online sections. It admits for fall only and accepts no transfer credits. Calculus II and linear algebra are required before entry.

Texas Tech has a one-year full-time plan. Students can take all 36 hours on campus or online. A two-year online plan cuts the term load. Both routes use the same fixed course order.

Students take statistics, databases, scripting, and machine learning. Big data security and business use also appear. The required Data Science Project puts those skills to work.

The fixed order gives little room for a missed class. One-year students also take short summer courses. Spring entry is part-time and online only. The start term changes the route.

Rice requires code, statistics, and data visualization. Big data and machine learning are also required. A four-credit capstone joins those subjects. Students use them in an applied project. That plan earns full marks for course depth and applied work.

Each student picks one of five focus areas. The focus takes at least nine credits. Four paths cover business analytics, energy, image work, or sport analytics. Rice has campus and online routes. It limits how many credits can move between them.

The online route charges $1,700 per credit for fall 2026 entry. That puts the 31-credit floor near $52,700 before other costs. Rice lists no aid for this MDS. Its Computer Science Department says the same. Ask for the full bill before you compare formats.

Applicants choose statistics, math, computer science, or electrical engineering. Everyone takes four core classes. They cover math, statistics, computing, and machine learning. Six electives give each track its focus.

The normal pace is three terms. Students take at least three electives in their home track. The other slots can come from participating departments.

The program admits for fall and runs on campus. Its capstone is an elective, not a degree rule. Read each track’s course list before you apply. Students stay in the track that admits them.

SMU has live web classes and self-paced work. Students take 33.5 credits in 20 to 28 months. The plan includes a two-credit capstone. It also has 1.5 credits of immersion work.

Students choose one of two focus areas. They are Machine Learning and Artificial Intelligence, or Decision Analytics. Set class times add more contact. That can suit students who dislike taped lessons.

Price puts this program last in the master’s group. Tuition starts at $37,855. The distance fee is $100 per credit. It lifts the floor to $41,205 before books or travel. Students must also attend two campus immersion events.