Why University of Virginia?
The online Master of Science in Data Science program at the University of Virginia is a relatively new entrant to the world of online data science education. It relies on the in-depth research expertise and stellar faculty of the University of Virginia, a large public research university in Charlottesville, Virginia. The program is selective, requiring students to have an undergraduate degree with a minimum 3.0 GPA. A bachelor’s degree in a specific subject area is not required. Still, applicants should have completed coursework in single variable calculus, linear algebra or matrix algebra, introductory statistics, and introductory programming. GRE or MCAT scores should be submitted with your application.
|University Name||University of Virginia|
|Name of Degree||Master of Science in Data Science|
|School or Department Administering Program||School of Data Science|
|Cost per credit||$1,242|
|Tuition for Entire Program||$48,000|
|Test Requirements||GRE or MCAT|
|Prerequisite Courses and Skills||
|Campus Visit Required?||No|
|Typical Time to Complete||Two years|
|When Can Students Start the Program?||Summer, Fall, Winter, Spring|
|Does the Program Include a Capstone?||Yes|
|Does the Program Include a Practicum or Internship?||No|
|Other Features that Make the Program Unique||
|Program Objectives (quoted directly from the program)||The Data Science program gives students the edge they need to perform at the highest levels of the field by producing three-dimensional data scientists. A data scientist uses quantitative and computational skills to create value from data – transforming and organizing it; analyzing it using computing, mathematics, and statistics; and converting it into valuable knowledge. But a three-dimensional data scientist complements quantitative and computational data skills with the ability to communicate effectively and act ethically.|
|Program Description||Thirty-two credits of coursework covering all aspects of the data science field prepare UVa students for careers in analytics and other areas. The emphasis throughout is on forming data scientists who are skilled in communication and ethically aware. The curriculum covers all stages of the data lifecycle from transformation to organization to analytics to visualization.|
What will I Learn?
All students in the program must complete the same courses, and there are no elective options. A distinctive feature of the program is the fact that students take several one-credit and two-credit courses in addition to more typical three-credit courses. This structure means that students can study more topics in-depth than in some other programs. The emphasis throughout the program is on forming “three-dimensional” data scientists, meaning data scientists who have the communication skills, ethical knowledge, and critical thinking skills to be leaders in their organizations.
Students begin the program with introductory courses in Programming and Systems and Foundations of Computer Science. Statistical knowledge is taught in Linear Models for Data Science. Two courses in machine learning are offered: Bayesian Machine Learning and general Machine Learning. Analytics skills are covered in Exploratory Text Analytics and Big Data Analytics. Advanced techniques are taught in Data Mining and Data Visualization. Two courses in Practice and Application of Data Science allow students to explore different problems and methods and develop their expertise. Students then have an opportunity to apply the skills and knowledge they have learned through a final capstone project exploring a data-intensive problem.
How much will the program cost?
Students finish their degree within two years and pay $1,242 per credit for a total of 32 credits, or $48,000
How does the program fit into my life?
The program is usually completed in 2 years. Students can begin the program in Summer, Fall, Winter, or Spring. In comparison with other data science Master’s programs, the University of Virginia program is less flexible since students are expected to attend one hour of scheduled instruction per week per course. The remainder of instruction is asynchronous, meaning that instructors create learning materials such as lectures, activities, quizzes, assignments, and group discussions in weekly modules, and students are responsible for completing the module on their schedule within the given week. Because of the project-based nature of the program, including the two semester-long capstone, students can expect to need to schedule time to work with classmates or meet with instructors.
The University of Virginia program provides an intensive and comprehensive introduction to the data science field. The program is particularly strong in the area of text analytics, a technique for which the university is well known in the areas of digital humanities and computer science. Students who are looking for a higher degree of in-person interaction will appreciate the opportunity for scheduled synchronous classes every week. The program assumes a higher level of quantitative preparation than some other degree programs. The price point may also limit the accessibility of the program. For those who do decide to apply, the University of Virginia degree offers lots of opportunities for practical application of skills and independent research.