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For aspiring data science professionals looking to gain advanced skills to manage, analyze, mine, and understand complex data to make strategic decisions.For aspiring data science professionals looking to gain advanced skills to manage, analyze, mine, and understand complex data to make strategic decisions.For aspiring data science professionals looking to gain advanced skills to manage, analyze, mine, and understand complex data to make strategic decisions.
DataScience@SMU is an online Master of Science in Data Science program designed for current and aspiring data science professionals looking to gain the advanced skills needed to manage, analyze, mine and understand complex data to make strategic decisions in their organizations. Through a combination of interactive coursework, collaborative group activities and online face-to-face classes, students gain the technical, analytical and communication skills needed to make meaningful data-driven decisions across various industries.
DataScience@SMU’s interdisciplinary curriculum draws from SMU’s Dedman College of Humanities and Sciences, Lyle School of Engineering and Meadows School of the Arts. Classes and coursework focus on statistics while building and expanding upon computer science and data visualization skills. As students progress in the program, they master more advanced concepts and have the opportunity to choose a specialization with a customized curriculum that closely aligns with their goals.
By choosing an area of specialization, students can master necessary skill sets and apply them directly to their career interests.
Master the machine learning techniques needed to build self-optimizing systems and provide solutions to problems or improve processes in any organization. Learn more about the Machine Learning and Artificial Intelligence Specialization.
Master the analytical tools required to synthesize qualitative data and effectively communicate results to key stakeholders to inform strategic decision-making. Learn more about the Decision Analytics Specialization.
Evaluates the foundational theory and applications of Artificial Intelligence (AI), including deep learning, generative AI, and reinforcement learning. Covers key techniques such as transformer models, prompt engineering, retrieval augmented generation (RAG), multi-agentic frameworks and AI ethics, with a focus on real-world deployment across industries. Hands-on projects reinforce concepts using state-of-the-art AI frameworks. With the fast moving pace of innovation in generative AI, this course is constantly updated to reflect the state of the art; the lead professor is the Vice President of Data Science at AT&T: Dr. Mark Austin.
Analyzes machine learning and the data preparation workflow, including multivariate nonlinear nonparametric regression, supervised classification, unsupervised classification and deep learning. All material covered is reinforced through hands-on experiences using state-of-the-art tools to design and execute machine learning and AI processes using Python and R.
Explores natural language processing (NLP) as applied to data mining, text mining and machine learning tasks with unstructured big data. Topics include document clustering and classification, automated tagging and highlighting, semantic search and text normalization to support machine learning applications. Students will gain experience building solutions from real-world data sets, utilizing WordNet and the data of some leading websites.
This course teaches students to effectively communicate data-based inference and insight through compelling data visualizations and presentations using tools like Tableau, Canvas and PowerPoint. Students learn to convey these complex insights to diverse audiences, including technical and executive stakeholders, through in-person, remote and recorded presentations.
The field of data science is one of the fastest-growing and most in-demand fields in the world. DataScience@SMU students gain highly sought-after skills in working with unstructured data, big data processing, statistical analysis, text mining and machine learning. With the ability to synthesize findings into actionable results for their organizations, our graduates are able to enter the data science field as candidates with a competitive edge.
The increased need across industries for data science professionals has made it one of the most desirable fields for skilled professionals.
Students looking to build their professional network and cultivate career opportunities after graduation can take advantage of the close connection that DataScience@SMU has with the emerging tech hub of Dallas, Texas. With a strong tech and health care industry presence and headquarters of companies such as AT&T, id Software, and Toyota (US), the Dallas region is becoming an attractive destination for talented data scientists.
The Dallas-Fort Worth Area employment market continues to grow. In November 2022, job growth rate doubled the national average at 6.1%1, and the most jobs were added in the Professional and Business Services sector, according the Bureau of Labor Statistics. The Dallas-Fort Worth area was third in the nation in net job growth in 2022 behind only New York and Los Angeles.
The average salary of computer and information research scientists in the Dallas-Fort Worth metro area is $151,6502. Texas is the third-highest paying state for this occupation.
DataScience@SMU gives you the ability to earn your degree and advance your career without relocating. As a student in the program, you are a full member of the SMU community with access to high-quality curriculum, faculty and resources.
Develop relationships with industry professionals, faculty and peers while working on group projects, networking at in-person immersions and engaging in discussion during live classes.
Stay connected through our virtual campus. Easily access your coursework from any Internet-enabled device and attend live, weekly classes. With a small student-to-faculty ratio, each class fosters rich, engaging discussions.
Receive dedicated student support with tutoring, refresher courses, and academic and career services to ensure your personal and professional goals are met.
Designed for working professionals, the program provides flexibility that enables you to maintain current responsibilities while earning your degree in two years or less. There is no GRE requirement for this program.
Have you completed our online SMU Data Science Boot Camp? As an alum, you may be eligible
to receive up to 6 credit hours in the Master of Science in Science Data program.
Learn more about the application requirements for SMU Data Science Boot Camp alumni.
There are four cohort start dates a year. The final deadline for the September 2025 cohort is June 27, 2025.
Applications for DataScience@SMU are evaluated holistically.
Get started. Begin your Master of Science in Data Science application.
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