Data Science Graduate Certificate
Derive predictive insights by applying advanced statistics, modeling, and programming skills. Acquire in-depth knowledge of machine learning and computational techniques. Unearth important questions and intelligence for a range of industries, from product design to 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.
Prior knowledge in statistics and basic programming is recommended for this certificate. If you do not have a strong background in statistics, start with an introductory statistics course, such as STAT E-100 before beginning this certificate.
The Data Science Certificate will be difficult for students with no prior knowledge of Python. If you do not have a background in programming, you should consider first taking CSCI E-7. You may wish to consider our Programming Certificate.
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:
- One statistics course (choose one from select group)
- Two electives (choose any two courses from select group)
- One required data science course (choose one from select group)
Determine the course progression that is right for you using our recommended course paths.