Advance Your Career With Specialized Data Science Skills
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.
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 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.
Machine Learning Specialization
Master the machine learning techniques needed to build self-optimizing systems and provide solutions to problems or improve processes in any organization. Learn more.
Business Analytics Specialization
Master the analytical tools required to synthesize qualitative data and effectively communicate results to key stakeholders to inform strategic decision-making. Learn more.
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 data mining processes using Python and R.
Natural Language Processing
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.
Examines the practical applications of the use of data sciences in the application of econometrics and quantitative finance. The primary learning framework is based on utilization of real and simulated data sets for business and economic situations. Students become familiar with the use of R in the creation of data analysis combining financial theory and statistical analysis, including portfolio theory, CAPM and econometric modeling.
Why Data Science? 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.
Dallas: The Emerging Hub of Data Science 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, Lockheed Martin, and Toyota (US), the Dallas region is becoming an attractive destination for talented data scientists.
Ranked the No. 1 Best Big City for Jobs by Forbes in 20181, the Dallas-Plano-Irving metro area has benefited from a 25.6 percent population increase since 20062 and a growing list of local tech startups. According to Emsi’s 2017 Talent Attraction Scorecard3, this vibrant startup environment has the attention of professionals from around the country, ranking as the No. 1 metro area for talent attraction based on its strong growth in jobs, migration, and educational attainment.
In addition, according to the Bureau of Labor Statistics, the average salary of computer and information research scientists in the Dallas-Fort Worth metro area is $95,2904.
25.6% Population growth from 2006 to 2018
$95,290 Average salary for computer and information scientists in 2017
No. 1 City for talent attraction
An Engaging Online Learning Experience
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.
DataScience@SMU at a Glance
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
Apply by November 9, 2018 to join the January 2019 cohort.