The graduate Certificate in Data Science and Applied AI is designed for students who desire a sequence of graduate-level courses that focus specifically on Data Science and Artificial Intelligence and that can be accessed both online and in-person for maximum flexibility.
Data Science - the analysis of data from any discipline to extract meaningful insights for strategic, operational, and tactical decision making - is increasingly in demand in business, economics, the sciences, politics, and many other disciplines. Faculty members from across campus team up to deliver this program collaboratively, reflecting the multidisciplinary nature of this field. Artificial Intelligence leverages insights from data science to enhance the capabilities of human decision makers.
The Certificate requires 15 credits across five courses, with one course in each of the categories: data science, statistics, programming, and artificial intelligence, and one other course selected to reflect the student’s primary area of interest.
Admission Requirements
Application Deadlines
Application deadlines vary by program, please review the application deadline chart for specific programs. Other important dates and deadlines can be found by using the One Stop calendars.
Admission
The minimum GPA for admission is 2.75 in a prior bachelor’s or post-baccalaureate degree (or cumulative credits after admission to a dual bachelor-master’s degree program). Applications must include a reason statement, at least one letter of recommendation, and other materials as specified in the graduate application system. Incomplete applications will not be considered. Students applying to the program are expected to have proficiency, demonstrated through coursework, exams, or a portfolio, in the following areas: Linear Algebra (3 credits), Multivariable Calculus (4 credits), Statistics (3 credits), and Computer Literacy (6 credits). Those without these proficiencies may be admitted when they have 6 credits or fewer of the proficiency requirements remaining to be completed, but proficiency coursework does not count towards the Certificate.
Application
- Students wishing to obtain this certificate must declare their intention by applying to the program office or director.
- All graduate certificate applicants—even those already enrolled in a UWM graduate program—must apply to the Graduate School.
- Graduate degree and previously admitted graduate non-degree students who decide to pursue a certificate program must submit the application before completing 6 credits in the certificate sequence.
- Applicants must possess a baccalaureate degree and have a minimum 2.75 cumulative undergraduate grade point average to be admitted into a certificate program.
Credits and Courses
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.
| Code | Title | Credits |
|---|---|---|
| Data Science | ||
| Select one of the following: | 3 | |
| Introduction to Data Science | ||
| Ideas and Applications of Data Science in Different Fields | ||
| Predictive Analytics for Managers | ||
| Introduction to Data Mining | ||
| Artificial Intelligence | ||
| Select one of the following: | 3 | |
| Artificial Intelligence for Business | ||
| Machine Learning for Business | ||
| Machine Learning and Applications | ||
| Introduction to Artificial Intelligence | ||
| Artificial Intelligence | ||
| Introduction to Machine Learning | ||
| Statistics Courses | ||
| Select one of the following: | 3 | |
| Statistical Methods in Atmospheric Sciences | ||
| Statistical Analysis | ||
| Data Analysis for Data Science | ||
| Introduction to Biostatistics | ||
| Programming Courses | ||
| Select one of the following: | 3 | |
| R Programming for Business Analytics | ||
| Introductory Programming Using Python | ||
| Programming for Machine Learning | ||
| Elective Course | 3 | |
Select one course from the MSDS curriculum subject to the approval of the Program Director, who will ensure curricular duplication is minimized. | ||
| Total Credits | 15 | |
Additional Requirements
Transfer Credit
The program follows the standard rules for certificates and allows up to three (3) credits of prior graduate-level coursework to be transferred. All transfer credits are subject to Graduate School transfer policy and must be
approved by the Program Director of the graduate Certificate in Data Science and Artificial Intelligence program.
Grade Point Average Requirement
In line with Graduate School policy, completion of the Certificate requires a cumulative GPA in program courses of at least 3.00.
Time Limit
Certificate requirements must be completed within four (4) years of initial enrollment in the program.
Articulation with Degree Programs
- Credits and courses required for a certificate may double count toward meeting UWM graduate degree requirements subject to the following restrictions:
- Degree programs must approve the courses from certificates that can double count toward the degree.
- All credits taken in completion of certificate requirements may count towards a UWM graduate degree as long as they do not contribute more than 90% of the total credits needed to obtain the degree. (Note: Students in PhD programs must still complete the minimum residency requirements)
- Certificate courses used toward meeting degree requirements must be completed within the time limit for transfer credit.
- Courses completed for a degree may be counted toward a subsequent certificate, subject to all certificate policy requirements.
- A course may count toward no more than one certificate and one degree.
- Students may not earn a certificate subsequent to a concentration in the same area.