Data Science Certificate
Learn how to analyze data to gain insights, develop new strategies, and cultivate actionable business intelligence in areas as diverse as product design, marketing, and finance.
Key learning outcomes
- Master key facets of data investigation, including data wrangling, cleaning, sampling, management, exploratory analysis, regression and classification, prediction, and data communication.
- Implement foundational concepts of data computation, such as data structure, algorithms, parallel computing, simulation, and analysis.
- Leverage your knowledge of key subject areas, such as game theory, statistical quality control, exponential smoothing, seasonally adjusted trend analysis, or data visualization.
No application is required. You simply register for graduate courses during our fall, spring, or summer registration periods.
Earning the Certificate
To meet the requirements for the certificate, you must:
- Complete four certificate courses for graduate credit.
- Earn at least a B grade in each course.
- Complete the courses within three years.
The professional graduate certificate in data science requires four courses:
- Three electives (choose any three from a select group)
- Introduction to Data Science (required)
View our sample course path to guide your course selection when pursuing this certificate.
Prior knowledge in statistics and programming is required for this certificate. This graduate certificate will be difficult for students with no prior knowledge of Python.
Courses taken before the 2013–14 academic year do not apply toward this certificate.