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Data Analytics Certificate

The Data Analytics Certificate is a three course sequence designed to provide students with the knowledge, skills, and tools needed  for counducting data analysis. Students learn to explore, analyze, and visualize data using computational thinking, programming skills, and applied statistics.

The core topics addressed by the certificate are:

  • algorithmic / computational thinking
  • communication (written and verbal)
  • data curation / management
  • ethics (privacy, informed consent, data security)
  • statistics / statistical inference
  • visualization

Specific skills developed through this certificate include:

  • data preparation skills using coding, including data cleaning, organization, and transformation
  • statistical analysis including descriptive statistics, exploratory analyses, inferential statistics, and modeling up through simple linear regression
  • data aggregation techniques including contingency tables (cross-tabs) and pivot tables
  • analysis and visualization for data-informed decision making
  • use of ‘business intelligence’ software (e.g. Tableau)
  • use of databases for retrieving data (database queries)

Course Requirements 

A minimum of three courses to include:

  • CS 125 / DASC 125 - Introduction to Computer and Data Sciences
  • One statistics course (BIOL 323, ECON 227, MATH 141, or PSYC227)
  • DASC 225 - Data Analytics with Visualization (only offered fall semester)

Course Substitutions

The following approved substitutions may count toward the certificate if any of the required courses are counted toward a student’s major or minor:

  • CS 314: Database Systems
  • DASC 377: Applied Data Analysis
  • ECON 328: Applied Econometrics
  • ECON 338: Time Series Analysis
  • MATH 215: Linear Algebra
  • MATH 403: Computational Data Analysis


Brad Sheese - Professor of Computer Science

Department - Computer Science