MS in Business Analytics and Artificial Intelligence

NA On Campus Masters Program

University of Texas Austin

Program Overview

The Master of Science in Business Analytics and Artificial Intelligence at The University of Texas at Austin is a STEM-designated graduate program designed to prepare students to use data, artificial intelligence, and advanced analytics to solve complex business problems. Offered through the McCombs School of Business, the program combines statistical analysis, machine learning, programming, optimization, and business strategy to help students transform technical insights into effective organizational decisions. Students can choose between a 10-month full-time on-campus format in Austin and a 23-month part-time online format designed for working professionals.

The program was previously called the Master of Science in Business Analytics (MSBA); the updated name took effect in August 2026.

Curriculum Structure

Summer Term: Data Science and Machine Learning Foundations

Students develop foundational skills in programming, data management, and machine learning. Core courses include Introduction to Machine Learning and Neural Networks and Data Science and Agentic Programming. Students work with Python and Pandas while learning data wrangling, visualization, classification, clustering, supervised and unsupervised learning, and model evaluation.

Fall Term: Advanced Analytics, Optimization, and Business Applications

Students advance their technical and business knowledge through courses such as Optimization for Decision Making, Information Management, Analytics for Unstructured Data, Financial Management, and Advanced Deep Learning and Machine Learning. These subjects introduce optimization methods, database technologies, generative AI applications, deep learning, and the use of analytical models in business decision-making.

Spring Term: Advanced AI and Applied Business Analytics

Students continue with advanced topics such as Unsupervised Learning and Dynamic Optimization and Reinforcement Learning. They explore clustering, dimensionality reduction, anomaly detection, simulation, dynamic programming, and reinforcement learning. Electives allow students to specialize in areas such as marketing analytics, supply chain analytics, finance analytics, and artificial intelligence.

Applied Learning: Business Intelligence Capstone

Students complete an industry-sponsored practicum through the Business Intelligence Capstone. Working in teams, they address real business analytics problems for a business sponsor, applying data modeling, technical tools, business knowledge, and analytical storytelling to develop practical recommendations.

The full-time program requires 36 credit hours and can be completed in approximately 10 months. The working-professional format also requires 36 credit hours but is completed over approximately 23 months.

Focus Areas

Business analytics, artificial intelligence, machine learning, deep learning, generative AI, agentic programming, predictive analytics, prescriptive analytics, descriptive analytics, data science, statistical analysis, data visualization, database management, Python programming, optimization, reinforcement learning, unstructured data analytics, business intelligence, financial analytics, marketing analytics, supply chain analytics, decision science, and responsible AI implementation.

Learning Outcomes

Graduates develop the ability to collect, manage, interpret, and analyze complex business data using advanced statistical and computational techniques. They learn to build and evaluate machine learning models, apply predictive and prescriptive analytics, use generative AI in business workflows, and develop optimization solutions for organizational challenges. Students also strengthen their ability to translate technical findings into actionable business recommendations, communicate analytical insights to decision-makers, and evaluate AI systems with attention to responsible deployment, privacy, security, and governance.

Professional Alignment

The program is STEM-designated, making eligible international graduates on F-1 visas potentially eligible for the 24-month STEM Optional Practical Training extension, subject to applicable U.S. immigration requirements. It is offered through the McCombs School of Business, which is accredited by AACSB International. The curriculum emphasizes industry-relevant competencies in analytics, machine learning, AI applications, and business decision-making. The university does not identify a separate professional certification that graduates automatically receive through this degree.

Reputation

The McCombs School of Business benefits from a large alumni network of more than 108,000 graduates and faculty expertise in analytics, statistics, information systems, and business. Its MS Business Analytics and AI curriculum is shaped with input from industry partners and includes applied learning through an industry-sponsored capstone project.

Potential career paths include business analyst, data scientist, analytics consultant, business intelligence analyst, digital marketing analyst, product manager, supply chain analyst, machine learning analyst, AI business analyst, operations research analyst, and decision science analyst.

The program's official webpage refers to strong demand for analytics and data science professionals, but it does not provide a specific program-level QS or Guardian ranking in the information reviewed.

Experiential Learning (Research, Projects, Internships etc.)

At the University of Texas at Austin, the Master of Science in Business Analytics (MSBA) program is designed to provide students with hands-on experience that translates theoretical knowledge into practical skills. The program emphasizes experiential learning through various opportunities that allow students to engage with real-world data and business challenges. With access to state-of-the-art facilities and cutting-edge tools, students are well-equipped to thrive in the fast-paced world of business analytics.

Here are some key components of the experiential learning opportunities available in the MSBA program:

- Data Analytics Lab: A dedicated space equipped with advanced software and tools for data analysis, including Python, R, Tableau, and SQL, allowing students to work on real datasets.

- Capstone Projects: Students collaborate in teams to tackle real business problems presented by industry partners, providing invaluable experience in applying analytics to drive decision-making.

- Internship Opportunities: The program encourages internships with leading companies, giving students the chance to gain practical experience and build professional networks.

- Field Trips: Students have the opportunity to visit local businesses and tech companies, gaining insights into how analytics is applied in various industries.

- Workshops and Seminars: Regularly scheduled workshops led by industry experts cover the latest trends and tools in business analytics, enhancing students' learning experience.

- Access to Libraries and Research Institutes: Students can utilize the extensive resources available at the UT Libraries and collaborate with research institutes focused on data science and analytics.

- Networking Events: The program hosts events that connect students with alumni and industry professionals, fostering relationships that can lead to job opportunities.

These experiential learning components are designed to ensure that graduates of the MSBA program are not only knowledgeable but also highly skilled and ready to make an impact in the field of business analytics.

Embarking on this journey at UT Austin will undoubtedly set you on a path to success in the dynamic world of business analytics!

Progression & Future Opportunities

The Master of Science in Business Analytics (MSBA) at the University of Texas at Austin equips graduates with the skills and knowledge to excel in a rapidly evolving data-driven landscape. Alumni of this program often find themselves in high-demand roles such as Data Analyst, Business Intelligence Consultant, and Operations Research Analyst. With a strong foundation in analytics, graduates are well-prepared to tackle complex business challenges and drive strategic decision-making.

Here’s what you can expect in terms of progression and future opportunities:

- University Services: The MSBA program offers access to the Career Management team, which provides personalized career coaching, resume workshops, and networking events with industry leaders.
- Employment Stats and Salary Figures: According to recent data, over 90% of MSBA graduates secure employment within three months of graduation, with starting salaries averaging around $90,000.
- University–Industry Partnerships: The program has established partnerships with leading companies such as Dell, IBM, and Accenture, providing students with internship opportunities and real-world projects that enhance their learning experience.
- Long-term Accreditation Value: The MSBA program is accredited by the Association to Advance Collegiate Schools of Business (AACSB), ensuring that your degree holds significant value in the job market.
- Graduation Outcomes: Graduates have gone on to work for top firms in various sectors, including finance, healthcare, and technology, showcasing the versatility of the skills gained through the program.

Further Academic Progression: After completing the MSBA, students have the option to pursue further studies, such as a Ph.D. in Business Analytics or related fields, which can lead to academic careers or advanced research positions. Additionally, graduates may choose to specialize further by obtaining certifications in data science, machine learning, or other relevant areas, enhancing their expertise and career prospects even more.

The MSBA program at UT Austin not only prepares you for immediate success in the workforce but also lays the groundwork for lifelong learning and advancement in your career.