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Graduate Certificate in Data Analytics

The Graduate Certificate in Data Analytics is offered collaboratively by Virginia Tech's Departments of Computer Science, Electrical and Computer Engineering, and Statistics. This certificate prepares students for technical careers in big data analytics and data science. Students will acquire in-depth technical skills that will enable them to understand the underlying technical fundamentals of data analytics, to develop new analytical methods, and to engineer new analytical tools. Students acquire skills that integrate computational, statistical, and engineering techniques that form the heart of big data analytics. This certificate provides students with formal recognition of their skills to better support their career prospects.

There is a growing need for technically trained engineers and scientists to lead the rapidly evolving field of big data analytics. The U.S. presidential administration has identified big data analytics as a core area of national need. Data science is one of the fastest growing career paths, and demand for technical expertise is out-pacing supply. Technical expertise is needed to develop new methods, tools, and infrastructures required to support novel big data analytics operations in industry, government, and academia. The technical expertise required involves a combination of computation, statistics, and engineering, such that training in any one of these individual disciplines alone does not suffice. This certificate serves to train technical students with a broader view across these disciplines to support the data analytics field.

The learning outcomes of Data Analytics certificate program:

  • Students will have technical depth in the fundamentals of data analytics, in terms of understanding the underlying principles and implementations of analytical methods.
  • Students will have broad understanding of multi-disciplinary perspectives on technical methods in data analytics, including computational, statistical, and engineering perspectives.


Students should complete at least 2 courses from the core list (see below) and 2 courses from the elective list, for a total of 12 credits. The set of courses taken must span all three of the host departments (CS, ECE, STAT). All courses must be graded A-F, and students must attain a minimum 3.0 GPA in the designated courses. Transfer credits are not permitted. At most 6 of the credits can be double counted toward the student's degree program.


Core Courses: (Choose 2)

  • CS/STAT 5525 Data Analytics I
  • CS/STAT 5526 Data Analytics II
  • CS 5824/ECE 5424: Advanced Machine Learning

Restricted Elective Courses: (Choose 2)

  • CS 5234 Advanced Parallel Computation
  • CS 5604 Information Storage and Retrieval
  • CS 5614 Database Management Systems
  • CS 5764 Information Visualization
  • CS 5804 Introduction to Artificial Intelligence
  • CS 6604 Advanced Topics in Data and Information
  • STAT 5114 Statistical Inference
  • STAT 5314 Monte Carlo Methods in Statistics
  • STAT 5414 Time Series Analysis I
  • STAT 5444 Bayesian Statistics
  • STAT 5444G Advanced Applied Bayesian Statistics
  • STAT 5504 Multivariate Statistical Methods
  • STAT 5544 Spatial Statistics
  • ECE 5524 Pattern Recognition
  • ECE 5554 Computer Vision
  • ECE 5606 Signal Detection and Estimation
  • ECE 5734 Convex Optimization
  • ECE 6504 Deep Learning for Perception
  • ECE 6554 Advanced Computer Vision
  • CS6424/ECE6424 Probabilistic Graphical Models and Structured Prediction


For more details, see the Graduate Certificate in Data Analytics page.

The Data Analytics certificate is administered by the Discovery Analytics Center. Please contact DAC for more information on the Graduate Certificate in Data Analytics.