This certificate is designed to enhance the skills of engineering students in the field of Data Analytics, which is in high demand across all engineering fields. Students may choose from a wide variety of courses from each of the four main areas: Foundations of Data Analytics, Applications of Data Analytics, Data Science, and Machine Learning. The culminating course in the program focuses on ethical issues in Data Analytics and provides students with principled solutions to address these modern societal challenges.
The program is open to any degree-seeking undergraduate engineering student with a plan of study that fulfills the certificate requirements. Applications can be submitted at any time, but students are encouraged to apply early to ensure a smooth and successful completion of the program.

How to Get in

All current undergraduate students in the College of Engineering are eligible to complete the Certificate in Engineering Data Analytics. Students should meet with the Certificate Advisor to discuss their intention to pursue the certificate and submit an online declaration form: https://engineering.wisc.edu/programs/certificates/engineering-data-analytics/declaration.

Students declared in the Certificate in Data Science are not eligible to declare the Certificate in Engineering Data Analytics.


Select one course from each area. The ethics course must be taken after the other four courses are completed.

Foundations of Data Analytics3
Applications of Data Analytics3-4
Data Science3
Machine Learning3
Ethics (Complete last)3
Ethics of Data for Engineers
Total Credits15

Foundations of Data Analytics

E C E 203 Signals, Information, and Computation3
E C E 204 Data Science & Engineering3
E C E 331 Introduction to Random Signal Analysis and Statistics3
I SY E 210 Introduction to Industrial Statistics3
I SY E 312 Data Management and Analysis for Industrial Engineers3
I SY E 412 Fundamentals of Industrial Data Analytics3

Applications of Data Analytics

E C E 334 State Space Systems Analysis3
E C E 431 Digital Signal Processing3
E C E 432 Digital Signal Processing Laboratory3
E C E 454 Mobile Computing Laboratory4
E C E/​COMP SCI  533 Image Processing3
I SY E/​M E  512 Inspection, Quality Control and Reliability3
I SY E 517 Decision Making in Health Care3
I SY E 575 Introduction to Quality Engineering3
M S & E 401 Special Topics in Materials Science and Engineering (Topic: Data Science in Materials)3

Data Science

E C E/​COMP SCI/​I SY E  524 Introduction to Optimization3
E C E/​COMP SCI  561 Probability and Information Theory in Machine Learning3
I SY E 516 Introduction to Decision Analysis3
I SY E 620 Simulation Modeling and Analysis3
I SY E 624 Stochastic Modeling Techniques3
I SY E/​MATH/​OTM/​STAT  632 Introduction to Stochastic Processes3

Machine Learning

E C E/​COMP SCI/​M E  532 Matrix Methods in Machine Learning3
E C E/​COMP SCI/​M E  539 Introduction to Artificial Neural Networks3
I SY E 521 Machine Learning in Action for Industrial Engineers3
I SY E 562 Human Factors of Data Science and Machine Learning3


I SY E/​E C E  570 Ethics of Data for Engineers3

Certificate Completion Requirement

This undergraduate certificate must be completed concurrently with the student’s undergraduate degree. Students cannot delay degree completion to complete the certificate.

Learning Outcomes

  1. Apply tools and methods to understand, analyze, and interpret data from a variety of sources
  2. Apply tools and methods to draw conclusions from and make decisions based on analysis of data
  3. Articulate the potential impact of a data-driven decision in the context of ethics, fairness, and equity
  4. Identify how engineers apply data analytics in practice using machine learning, data science, and other fundamental tools of data analytics