Multidisciplinary Data Analytics and Applied Artificial Intelligence Undergraduate Certificate
There is data all around us, and every day artificial intelligence (AI) can do more to help analyze it. Businesses want to hire people who can leverage AI to manage, analyze, and use a wide range of data for more effective decision making. The Undergraduate Certificate in Multidisciplinary Data Analytics and Applied AI is designed for you to learn those skills.
The Undergraduate Certificate in Multidisciplinary Data Analytics and Applied AI is a special program that includes courses from the College of Letters & Science, the College of Community Engagement & Professions, the Lubar College of Business, and the College of Engineering & Applied Science. Faculty members from across campus team up to deliver this program collaboratively, reflecting the multidisciplinary nature of this field.
The Undergraduate Certificate in Multidisciplinary Data Analytics and Applied AI at UWM is unique because its goal is to train students to practice data analytics and use AI in whatever field they are passionate about. The Certificate requires 15 credits across five courses, with one course in each of the categories: data science, artificial intelligence, statistics, and programming, and one other course selected to reflect the student’s primary area of interest.
The career prospects for individuals with data analytics and AI skills are very positive. Data analytics skills are being used not only in industries that are obviously oriented toward using data, like information technology, sciences and business, but also in fields that more recently have begun to take full advantage of their data resources, like agriculture, atmospheric sciences, environmental sciences, geography, and healthcare.
Program Type
Undergraduate Certificate
Program Format
On Campus
Requirements
The Certificate requires 15 credits across five courses, with one course in each of the four categories: data science, artificial intelligence statistics, and programming, and one other course selected to reflect the student’s primary area of interest.
| Code | Title | Credits |
|---|---|---|
| Data Science (select one): | 3 | |
| Data Analytics | ||
| Introduction to Data Mining | ||
| Introduction to Database Systems | ||
| Applied Water Statistics and Data Manipulation | ||
| Data Analysis and Visualization for the Information Professional | ||
| Introduction to Data Science | ||
| Introduction to Statistical Computing and Data Science | ||
| Artificial Intelligence (select one): | 3 | |
| Business Intelligence | ||
| Machine Learning and Applications | ||
| Introduction to Artificial Intelligence | ||
| Applied Web 3.0: Artificial Intelligence and Blockchain | ||
| Statistics (select one): | 3 | |
| Statistical Methods in Atmospheric Sciences | ||
| Economic Forecasting Methods | ||
| Statistics for Economists | ||
| Introduction to Econometrics | ||
| Data Analysis for Data Science | ||
| Introduction to Mathematical Statistics I | ||
| Programming (select one): | 3 | |
| Introduction to Programming and Modeling in Ecology and Evolution | ||
| Introduction to Business Application Development | ||
| Introductory Programming Using Python | ||
| Intermediate Computer Programming | ||
| Introduction to Application Development | ||
| Select one additional course from any one of the four areas 1 | 3 | |
| Total Credits | 15 | |
- 1
For this one elective course, consult with the BSDA program director to select one course from the BSDA curriculum. You need approval of the Program Director, who will ensure duplication of course content is minimized.
To obtain the certificate, the student must complete, with a minimum grade point average of 2.75, at least 15 credits in approved Multidisciplinary Data Analytics and Applied AI Certificate courses, of which 12 must be earned in residence at UWM. The certificate will be confirmed upon completion of the certificate requirements. Certificate courses may not be taken on a credit/no credit basis.
Students earning the BS in Data Analytics or the BS in Data Science are not eligible to earn this certificate.
Spring 2026: Upcoming Courses in Program
Check catalog for compatibility - https://catalog.uwm.edu| Course Code | Course Title |
|---|---|
| BUS ADM 335 | Introduction to Business Application Development
|
| BUS ADM 536 | Business Intelligence
|
| COMPSCI 202 | Introductory Programming Using Python
|
| COMPSCI 251 | Intermediate Computer Programming
|
| COMPSCI 411 | Machine Learning and Applications
|
| COMPSCI 422 | Introduction to Artificial Intelligence
|
| COMPSCI 422G | Introduction to Artificial Intelligence
|
| COMPSCI 557 | Introduction to Database Systems
|
| COMPSCI 557G | Introduction to Database Systems
|
| ECON 411 | Economic Forecasting Methods
|
| ECON 411G | Economic Forecasting Methods
|
| FRSHWTR 585 | Applied Water Statistics and Data Manipulation
|
| FRSHWTR 585G | Applied Water Statistics and Data Manipulation
|
| INFOST 350 | Introduction to Application Development
|
| INFOST 350G | Introduction to Application Development
|
| INFOST 370 | Data Analysis and Visualization for the Information Professional
|
| INFOST 582 | Introduction to Data Science
|
| INFOST 582G | Introduction to Data Science
|
| INFOST 671 | Applied Web 3.0: Artificial Intelligence and Blockchain
|
| INFOST 671G | Applied Web 3.0: Artificial Intelligence and Blockchain
|
| INFOST 687 | Data Analysis for Data Science
|
| INFOST 687G | Data Analysis for Data Science
|
| MTHSTAT 361 | Introduction to Mathematical Statistics I
|
| MTHSTAT 361G | Introduction to Mathematical Statistics I
|
Certificates are similar to minors and generally require the completion of six to eight classes. Unlike a minor where all of the classes come from a single subject area, the classes come from multiple subject areas related to the theme of the certificate. Certificates are typically earned in conjunction with a degree though some certificates are available as a standalone credential.