Data Analysis Certificate
students: earn a validated Certificate in Data Analysis in approximately 10–15 hours, self-paced. A limited number of seats remain.
For UT Austin students:
14-day withdrawal (full refund) before completion
Self-paced · Start immediately
Students can enroll at heavily discounted prices through the enrollment deadline -
from $299 to $99.00
students are eligible through August 31st, 2026.
Enrollment closes at 11:59 PM CT. If you plan to enroll, we recommend completing
enrollment before the deadline.
Why this certificate matters
96%
Employers suggest certificates strengthen applications
$12K
Average reported salary increase with certificate
9/10
Hiring managers prioritize candidates with certificates
Based on industry surveys and self-reported outcomes from certificate program completers.
Individual results may vary.
Program Overview
Overview
Key Features
Audience:
Students in related fields, including sciences, speech and hearing science, engineering, statistics, radiologic technology, data science, business, public health, computer science, and mathematics, will often find the program highly relevant to their coursework and career interests. The program focuses on data analysis concepts and methods related to data cleaning, exploratory analysis, visualization, statistical reasoning, and insight-driven decision support. The program is appropriate for any student who wants to strengthen their résumé, present more complete job applications, or develop a deeper understanding of analytical thinking and data-driven problem solving.
Duration:
Four months of access per semester to course materials and resources. At the end of four months, you can renew your access if needed.
Time to Complete:
Expected to be completed within 10 to 15 hours, allowing for flexible, self-paced learning.
Certificate:
Certificate in Data Analysis.
Why This Certificate Matters:
Data analysis skills appear in job descriptions across industries. This certificate provides a clear and credible way to demonstrate analytical ability, readiness for data-driven roles, and the skills employers desire and expect.
