Artificial Intelligence for Engineering Data Analytics Capstone

Capstone Certificate in Artificial Intelligence for Engineering Data Analytics

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Is this program right for you?

This flexible online program is built for engineers and technical professionals who work with data and want to strengthen their skills in AI, machine learning, and engineering-specific analytics. Complete the program in just two or three semesters — without disrupting your career.

  • Build in-demand skills in AI, machine learning, and engineering data analytics
  • Apply what you learn to real-world problems through hands-on projects
  • Complete the program 100% online in two or three semesters
  • Prepare to lead or support AI-driven initiatives in engineering settings

Education that works for you

Designed for working professionals, this online program offers flexibility without sacrificing depth. Courses feature live sessions, hands-on projects, and real-world applications in engineering data and AI.

Program type

Capstone certificate

Collection of courses in a single discipline, does not result in a degree

Explore program types

Certificate awarded

Capstone Certificate in Artificial Intelligence for Engineering Data Analytics

Commitment

2-3 semesters

Tuition

$1,300 per credit.

Beginning Fall 2026: $1,100 per credit with an automatic $100 per credit Wisconsin Resident Scholarship.

Format

Online

Primarily online

Credits

9 graduate-level credits

Admission terms

Program admits for fall, spring, and summer

STEM opt eligible

No

Supports F-1 Visa

Application deadlines

Summer 2026

  • Deadline: June 1, 2026
View UW-Madison’s Guide

Your questions, answered

Have questions? Fill out this form and we’ll get in touch!

Admissions and events

Program requirements

All applicants must:

  • Have a bachelor of Science degree in engineering from an ABET-approved program*
  • Have a minimum undergraduate GPA of 2.75 on the last 60 credits of degree
  • Submit evidence of English language proficiency, if applicable. See the Graduate School Requirements for more information

 

* Interested applicants with BS degrees in related fields should contact the Graduate Academic Advisor for more specific admission information at  studentservices@interpro.wisc.edu.

The admissions committee considers exceptions to standard requirements on an individual basis.

Application materials required

  • Online application
  • Resume/CV
  • Transcripts
  • Optional: submit up to two letters of recommendation

For complete application details visit UW–Madison’s Guide →

June 9, 2026 from 12 p.m. to 12:30 p.m.

Live Webinar: Online Engineering Graduate Programs Overview

Join program staff to learn more about the online engineering graduate programs including master’s and capstone certificate options.

Register now →

July 14, 2026 from 5 p.m. to 5:30 p.m.

Live Webinar: Online Engineering Graduate Programs Overview

Join program staff to learn more about the online engineering graduate programs including master’s and capstone certificate options.

Register now →

August 11, 2026 from 12 p.m. to 12:30 p.m.

Live Webinar: Online Engineering Graduate Programs Overview

Join program staff to learn more about the online engineering graduate programs including master’s and capstone certificate options.

Register now →

Results that work for you

Artificial Intelligence for Engineering Data Analytics Capstone

27 years

of delivering interactive online education

#6

Best Online Graduate Certificates in Artificial Intelligence

MastersInAI.org, 2026

#11

Online Graduate Engineering Program

U.S. News & World Report, 2026

What you’ll learn

Gain applied experience in AI tools, engineering analytics, and ethical data use. You’ll explore machine learning techniques, predictive modeling, and how to turn complex engineering data into actionable insights.

For complete curricular details visit UW-Madison’s Guide →
  • AI-driven data analysis and decision-making
  • Predictive modeling for engineering problems
  • Machine learning methods for technical systems
  • Automation and optimization using AI tools
  • Visualization and interpretation of complex data
  • Responsible and ethical use of AI in engineering

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