Data Science Certificate

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Analytics for the Environment

Program Information

The Data Science for Environmental Applications Certificate is a nine-month online program geared towards those pursuing a career in data analysis and modeling. Environmental professionals need to be able to make sense of large and complex data. Learning to handle, visualize, analyze, and make predictions with big data is a prerequisite for careful decision-making in agencies, non-governmental organizations, and consulting.


Whether you are a recent graduate or an established professional, this certificate will help you to develop and improve your quantitative toolkit for analyzing environmental data. The emphasis throughout will be on applied methods to increase job-ready skills.


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Learn Critical Techniques

All courses will be taught in an open source environment using R, R markdown, and Shiny.

The certificate combines three core courses in statistics with three seminars in key areas of data science. All aspects of the certificate have an emphasis on environmental applications.

Core Courses (4 credits each)

  • Applied Statistics
  • Multivariate Methods
  • Time Series Analysis (offered in odd years) or Spatial Analysis (offered in even years)

Topical Seminars (2 credits each)

  • Data Wrangling and Visualization
  • Machine Learning
  • App and Dashboard Development
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Develop Job-Ready Skills

The world of environmental data analysis is growing exponentially. Every day more and more data are available, and scientists need a variety of statistical techniques to think quantitatively about the world around them.

Online program delivery accommodates working professionals, allowing you to put your skills to work right away.

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Earn Graduate Credit

The Data Science for Environmental Applications certificate will improve your toolkit for visualizing, analyzing, and making predictions with environmental data.

Earn the certificate on its own, or add it to your graduate degree with face to face options.

Cohorts begin every September and complete the certificate in June. 

Application Requirements

  • A bachelor's degree with completion of a 300-level statistics course
  • Current graduate students adding the certificate to their in-progress master's degree apply here.
  • New applicants must complete the Graduate School's ApplyWeb application and pay the $100 application fee.
  • Within the application you will be prompted to upload an unofficial transcript from each institution attended.
  • Additional application materials for all applicants are specified below. Applications will not be forwarded to the department for review until all required materials have been received by the Graduate School.
  • International Applicants: Please review the requirements for Degree Equivalency and English Language Proficiency. This program is delivered online and may not meet student VISA requirements.

Additional Application Requirement

  • A one page statement of purpose that addresses the following: 1) Your academic background and how it has prepared you for a certificate in data science; 2) Motivations for pursuing the certificate, and area of specialization that you are interested in; 3) Research interests, or applicability of data science in the professional sector.

Financial Information

The cost for this program is the current Academic Self-Sustaining Graduate rate (noted under the "Location - State Support, Location - Self-Sustaining, & Academic Year - Self-Sustaining Programs" heading).

This certificate program is not eligible for federal student aid, but there are other funding options you may want to explore. If, however, these classes are taken in conjunction with the requirements for an MA or MS degree program, federal student aid may be applied toward your tuition costs.


Pursuing the Data Science Certificate was one of the smartest career moves I have made. I went from being a temporary employee to a permanent technician in a horticultural lab almost strictly because of my background in data science. I have since created figures for papers, had a role in data analysis on many projects, and am currently assisting a statistician on building predictive models and an app for growers to use to manage their pollination needs. Learning proper data management has also been a critical practice being a lab technician. It really builds on useful, professional skills that are an amazing addition to your toolbox and was also so much FUN. I had a blast with the assignments where there was some creative freedom allowed, such as making maps or other types of visualizations. I found a sense of “style” in figure making that I still use today. The professors are wonderful and are full of knowledge on these subjects. I would recommend it to anyone who plans be working with any sort of environmental data, or really any data for that matter.

Emma Rogers