DataScience@SMU is an online Master of Science in Data Science designed for current and aspiring data science professionals. Through a combination of interactive coursework, collaborative group activities and online face-to-face classes, you will gain the technical, analytical and communication skills you need to make meaningful data-driven decisions.
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.
A Skills-Based Curriculum
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, computer science, strategic behavior and data visualization skills so you can drive decision-making and advance in careers across industries.
Introduces data mining topics with an emphasis on understanding concepts through applied, hands-on implementation exercises. Includes related topics such as machine learning, data warehousing and dimensional modeling.
Introduces machine learning and the data preparation workflow covered – including multivariate non-linear non-parametric 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 data mining processes using Python and R.
An overview of fundamental cloud topics such as virtualization, IaaS, PaaS, and DevOps, students will work with current technologies that make the cloud possible – learn top cloud service providers, the “as a service” deployment model, and selective big data tools. Students will also get a high-level overview of NoSQL, and big data topics such as Hadoop, MapReduce, Pig, Hive, and Spark.
Designed for working professionals, the program provides flexibility that enables you to maintain current responsibilities while earning your degree in two years or less. GRE waivers are available for students with five or more years of professional experience.
20–28 months to complete the program
33.5 credits of coursework
3 start dates per year
A Student Community of Professionals
The program attracts a network of accomplished professionals in a range of industries across the nation. As a member of this community, you will work together, learn from shared experiences and apply the knowledge you gain directly to your career.