Graduate Certificate: Data Science and Applied Artificial Intelligence

CERTIFICATE IN DATA SCIENCE AND APPLIED ARTIFICIAL INTELLIGENCE

I. PROGRAM IDENTIFICATION

1.1 Title of Proposed Graduate Certificate:

Data Science and Applied Artificial Intelligence

1.2 Department(s) or Functional Equivalent(s) Sponsoring the Certificate:

The proposed program is sponsored by a faculty oversight committee (FOC) composed of

affiliated faculty members teaching courses within the program. See Section 5.8 for a list

of participating faculty members.

1.3 College(s), School(s) or Functional Equivalent(s) Sponsoring the Certificate:

Graduate School

1.4 Timetable for Initiation. Fall 2024

II. RATIONALE

There is an increased demand for data science and artificial intelligence skills across all

economic sectors. According to the U.S. Bureau of Labor Statistics, the employment of

data scientists is projected to grow 35 percent from 2022 to 2032, much faster than the

average for all occupations. To address the increased demand, we propose a 15-credit

graduate certificate in Data Science and Applied Artificial Intelligence, consisting of one

course from each of the categories data science, statistics, programming, and artificial

intelligence, and one other elective course selected to reflect the student’s primary area of

interest. The Certificate’s intended population includes post-baccalaureate professionals

and graduate students seeking a complement to their existing degrees. Instructional

modes for courses in the program include in-person, online and hybrid options making it

accessible for students seeking different formats of instruction.

The Certificate will enhance graduates’ job skills, which will lead to more economic

opportunities. Because many of UWM’s graduates continue to work locally and within

the state of Wisconsin post-graduation, the Certificate will also have a positive impact on

the local and statewide economy. Additionally, the Certificate will strengthen UWM’s

relationship with the local and statewide business communities that are increasingly

seeking talent skilled in data science and artificial intelligence. The certificate will also

increase UWM’s post-baccalaureate student enrollment.

III. INSTITUTIONAL CONTEXT

3.1 Relationship to Mission of Institution

The UW-Milwaukee Select Mission Statement (https://uwm.edu/mission/) states: “To

fulfill its mission as a major urban doctoral university and to meet the diverse needs of

Wisconsin’s largest metropolitan area, the University of Wisconsin–Milwaukee must

provide a wide array of degree programs, a balanced program of applied and basic

research, and a faculty who are active in public service. Fulfilling this mission requires

the pursuit of these mutually reinforcing academic goals.” Among the several goals listed

in this statement, the Certificate program especially contributes to the following:

• To further academic and professional opportunities at all levels for women,

minority, part-time, and financially or educationally disadvantaged students.

• To establish and maintain productive relationships with appropriate public and

private organizations at the local, regional, state, national, and international levels.

• To promote public service and research efforts directed toward meeting the social,

economic, and cultural needs of the state of Wisconsin and its metropolitan areas.

• To provide educational leadership in meeting future social, cultural, and

technological challenges.”

The proliferation in the use of data science and artificial intelligence across all sectors of

the economy will increase professional opportunities for all students in the Certificate

program. UW-Milwaukee has an undergraduate population that is 35% first-generation

students and 32% students of color. By providing students with the opportunity to

continue their professional development, the proposed program will serve students’

higher education needs and thus serve these diverse student populations. This, in turn,

will expand and strengthen UWM’s relationships with both public and private

organizations seeking graduates with data science and artificial intelligence-related

skillsets. Additionally, graduates of the Certificate program will be well-trained to help

employers meet the technological challenges and opportunities presented by the growing

use of vast amounts of data in every sector of society.

The Certificate will also address important aspects of the goals of UWM’s 2030 Action

Plan including: “expanding collaborative and interdisciplinary scholarship and graduate

programs,” “infusing entrepreneurship, design thinking, and data science into faculty

research and graduate and undergraduate education,” and “strengthening sustaining

partnerships with community, industry, and other academic institutions.”

The Certificate provides students with an opportunity to explore data science as a field

before committing to a degree program. The Certificate will also improve graduates’

earnings and employability potential and will provide them with credits towards the

Master of Science in Data Science degree if they choose to continue their education.

3.2 Relationship to/Impact on Other UWM Programs

The Certificate will be a unique program at UWM as it will be the only interdisciplinary

Data Science and Applied Artificial Intelligence certificate at the graduate level. Other

UWM data science or artificial intelligence-related certificate programs offer courses

focused on a single discipline or subject matter.

For example, the College of Letters and Science offers a graduate Certificate in Applied

Econometrics and Data Analysis, of which the curriculum focuses on Economics

coursework with three of sixteen course electives from non-economics disciplines.

The College of Engineering and Applied Science also offers a graduate Certificate in

Artificial Intelligence and Machine Learning. Again, the curriculum entirely consists of

coursework in the College of Engineering and Applied Science.

The Lubar College of Business has a graduate Certificate in Business Analytics with

coursework in Business Administration or Business Management within Lubar. This

certificate focuses on business applications of analytics rather than data science and

artificial intelligence.

Finally, the School of Information Studies offers a graduate Certificate in Data Curation

that has some data science-related coursework (INFOST 582 G Introduction to Data

Science and INFOST 687G Data Analysis for Data Science) but all of its courses are

within the School of Information Studies, under the INFOST subject heading. The goal

of this certificate is data curation rather than data science and artificial intelligence.

The graduate Certificate in Data Science and Applied Artificial Intelligence’s curriculum

mirrors that of the MS in Data Science program- it is interdisciplinary and allows

students flexibility to create their own path based on one’s area of interests. The

curriculum includes courses in the following areas: Business Administration, Business

Management, Computer Science, Criminal Justice, Information Science and Technology,

Public Health, among others. Thus, recipients of this certificate will be able to practice

data science and artificial intelligence in one or more of many disciplines.

IV. NEED

Need Based on Market Demand:

As previously stated in Section II, data science and artificial intelligence skills and

knowledge will continue to be in demand for the years to come. A 2017 report from the

employment outlook firm Burning Glass produced jointly with IBM and the Business

Higher Education Forum, stated that in meeting the skills demand, “higher education

needs to be nimble and responsive, and its bachelor’s, graduate, certificate, and executive

level programs have to be responsive to workforce needs.” Now in 2023, with the data

science job market growth estimated at 35 percent from 2022 to 2032, the need for

flexible and varied degree and certificate programs is more compelling.

Additional evidence of demand is also seen in investments made by employers like

Northwestern Mutual that have provided significant resources of $40 million in the initial

establishment of the Northwestern Mutual Data Science Institute to support the launch

and growth of undergraduate and graduate programs related to data including data

science and data analytics. That initial investment was recently renewed for $35 million

over the course of the next five years.

Estimated Enrollment:

Current enrollment in the MS in Data Science program demonstrates a high and growing

level of demand for graduate programs in data science. The MS in Data Science program

enrollment has grown from 5 students during its first semester (Fall 2022) to 42 students

(Spring 2024). The Certificate’s intended population includes post-baccalaureate

professionals and graduate students seeking a complement to their existing degrees.

The proposed Certificate will add another education option for post-baccalaureate

professionals who are unsure about pursuing the MS in Data Science option. It allows

students the opportunity to take five graduate-level courses in the Certificate program and

then decide, at that point, if they choose to move on to the MS in Data Science degree

option and complete just five additional courses. The proposed Certificate will also

appeal to current graduate students seeking to complement their degrees.

Projected enrollments and graduations for the program over the next five years are

presented in Table 1. These projections are conservative based on enrollment trends in

data analysis courses taught in different departments and colleges at UWM from Fall

‘2015 to Spring and Summer ‘2021. By the end of Year 5, we expect about 150 students

to have enrolled in the program over its five years and a total of 103 students to have

graduated. These projections are based on an average retention rate of 70% each year

(which is more conservative than the 75% rate based on data for UWM). We also assume

that, during years 2 through 5, 65% of the students enrolled during that year (which will

be a mix of students who enrolled first in previous years and continuing, and students

enrolling for the first time during that year) will graduate. This results in an overall

graduation rate of 69% among all students entering the program which is in line with

assumptions made in other related programs. Although the Graduate School does not

currently have reliable overall data for graduation rates, this is consistent with their

conservative estimates of master’s graduation rates. Given the increasing demand for data

analysts, these numbers also assume that students enrolling in this program are net

additions to the campus’ current total matriculants.

Table 1: Five-Year Certificate Program Enrollment Projections

Comparable Programs in Wisconsin and Illinois:

In Wisconsin, there are a few data science-related graduate certificate programs.

Marquette University offers a 12-credit graduate certificate in data science. The

Marquette University certificate has a generalized curriculum of coursework in Data

Analytics, Data Intelligence, Data at Scale and Data Ethics and does not require courses

in statistics or programming and has no course electives. UW Extended Campus offers

an asynchronous online-only graduate Certificate in Data Science with general

coursework in Foundations of Data Science, Programming for Data Science, Data

Warehousing, Communicating About Data and Data Mining and Machine Learning. The

UW System Extended Campus certificate is very broad-based and does not provide

significant coverage of statistics, machine learning or artificial intelligence. UW-Madison

and UW-Parkside offer certificates in Data Science but for undergraduate students only.

In Illinois, the University of Illinois Urbana-Champaign (UIUC) has an undergraduate

data science certificate but no master's certificate broadly covering the subjects of data

science and artificial intelligence. UIUC only offers undergraduate business-related data

analytics certificates by sub-disciplines (Business Analytics, Human Resources,

Accounting). Illinois State University (ISU) offers a 3-course/9 credit Data Science:

Computer Science graduate certificate that is completely online. ISU’s graduate

certificate covers Big Data, Data Analytics and Mining, Introduction to Machine

Learning and Data Information and Visualization. Again, only three of the four courses

are required, and the program is fully online. Illinois Institute of Technology (IIT) offers

a 3-course/9 credit Data Analytics graduate certificate both online and in-person with

students selecting three courses out of a nine-course selection. Loyola University also

offers a 3-course/9 credit graduate certificate. As with many of the 9 credit certificates,

Loyola’s program is intended as an introduction to key elements of data science.

Southern Illinois University-Edwardsville's post-baccalaureate certificate in Data Science

requires 12 credits for completion but the courses are part of a set prescribed

Mathematical Statistics curriculum with no interdisciplinary options for students in core

areas. Northern Illinois University’s100% online graduate certificate in Data Science for

Business is exactly that- a 4-course curriculum focused primarily on data science and

business. It does not offer general data science courses or courses in other disciplines.

Finally, the University of Illinois-Springfield’s 16-credit graduate certificate in Data

Analytics has but one required course listed in its curriculum (Introduction to Machine

Learning) with the remaining four courses in the curriculum requiring approval by one’s

advisor. The UWM certificate will provide more guidance to students with multiple

course options in three required areas while at the same time providing flexibility in

course selection.

V. PROGRAM DESCRIPTION AND EVALUATION

5.1 Description:

5.1.1 Narrative Description:

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.

5.1.2 Define the nature of the program:

The Certificate in Data Science and Applied AI is a multidisciplinary graduate certificate

intended to broaden one’s knowledge in data science and artificial intelligence. The

graduate Certificate in Data Science and Applied AI is a single institutional Certificate

taught solely at UW-Milwaukee.

5.1.3 List learning objectives and competencies:

Students completing the certificate will:

(1) develop insights from data, for applications,

(2) learn how to work with large data sets,

(3) gain experience in computer programming for data science,

(4) gain skills in areas of data science such as artificial intelligence and machine learning,

and

(5) understand how to deal with uncertainty which is an inherent characteristic of data

science.

5.1.4 List the mode(s) of instruction (i.e. in-person, on-line, hybrid).

In-person, hybrid and online.

5.1.5 Discuss whether this certificate program prepares students for gainful

employment in a recognized occupation. If it does and is eligible for Title IV financial

aid, supply the following information:

• Occupations the program prepares students to enter

• Occupational profiles

• Costs for books and supplies

Not applicable.

5.2 Curriculum – Courses and Credits:

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.

Data Science courses (select one)

INFOST 582G Introduction to Data Science

BUS ADM 767 Ideas and Applications of Data Science in Different Fields

BUSMGMT 709 Predictive Analytics for Managers

COMPSCI 425G Introduction to Data Mining

Artificial Intelligence courses (select one)

BUS ADM 745 Artificial Intelligence for Business

COMPSCI 411G Machine Learning and Applications

COMPSCI 422G Introduction to Artificial Intelligence

COMPSCI 710 Artificial Intelligence

COMPSCI 711 Introduction to Machine Learning

BUS ADM 812 Machine Learning for Business

Statistics courses (select one)

ATM SCI 500G Statistical Methods in Atmospheric Sciences

BUSADM 754 Statistical Analysis

INFOST 687G Data Analysis for Data Science

PH 702 Introduction to Biostatistics

Programming courses (select one)

BUSMGMT 744 R Programming for Business Analytics

COMPST 702 Introductory Programming Using Python

COMPSCI 715 Programming for Machine Learning

Elective courses (select one course from the MSDS curriculum subject to the

approval of the Program Director, who will ensure curricular duplication is minimized).

5.3 Admission requirements and procedures: 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.) 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.

5.4 Allowance for transfer credit (if any): 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.

5.4 Completion requirements: In line with Graduate School policy, completion of the

Certificate requires a cumulative GPA in program courses of at least 3.00.

5.5 Time limit: Certificate requirements must be completed within four (4) years of

initial enrollment in the program.

5.6 Certificate conferral: The certificate will be confirmed upon completion of the

certificate requirements.

5.7 Program Administration: The Certificate program will be reviewed by a faculty

oversight committee (FOC). The FOC will be responsible for governance of the

Certificate. The Certificate will be managed by a Program Director appointed by the

FOC. The Certificate Program Representative will be the MSDS Program Director.

Curricular development and review will be conducted by the Faculty Oversight

Committee (FOC) and the Graduate Curriculum Committee. Program advising will be

handled by the Program Director, program advisor and by Graduate Faculty from

affiliated departments.

5.8 Participating Faculty:

Layth Alwan

Professor, Lubar College of Business

Dean's Research Fellow

Razia Azen

Professor, School of Education

Director, Consulting Office for Research & Evaluation

Director, Educational Statistics and Measurement MS/PhD

Amit Bhatnagar

Professor, Lubar College of Business

Director, PhD Program

Ronald E. Pawasarat Faculty Scholar

Suzanne Boyd

Associate Professor, Mathematical Sciences - General

Vytaras Brazauskas

Professor, Associate Chair, Actuarial Science

Avik Chakrabarti

Associate Professor, Economics - General

Woonsup Choi

Associate Professor, Geography - General

Jason Dietenberger

Lecturer, School of Information Studies

Peter Dunn

Distinguished Professor, Biological Sciences

Clark Evans

Professor, Chair, Atmospheric Sciences Program Coordinator,

School of Freshwater Sciences

Matthew Friedel

Senior Lecturer, Information Studies

Jonah Gaster

Assistant Professor, Mathematical Sciences - General

Donna Genzmer

Academic Staff Emerita, Geography

Daniel Gervini

Professor, Mathematical Sciences - General

Rina Ghose

Professor, Industrial and Manufacturing Engineering

Sanjoy Ghose

Judith H. and Gale E. Klappa Endowed Professor, Lubar College of

Business

Maria Haigh

Associate Professor, Information Studies

Thomas Holbrook

Distinguished Professor and Wilder Crane Professor of

Government, Political Science - General

Rohit Kate

Associate Professor, College of Engr. & Applied Sci.

Margaret Kipp

Associate Professor, Information Studies

Kundan Kishor

Professor, Department Chair, Economics - General

Sergey Kravtsov

Professor, School of Freshwater Sciences

Emily Latch

Professor, Biological Sciences

Jake Luo

Associate Professor, College of Health Sciences

Amol Mali

Associate Professor, College of Engr. & Applied Sci.

Xiangming Mu

Associate Professor, Information Studies

Derek Nazareth

Associate Professor, Lubar College of Business

Purushottam Papatla

Northwestern Mutual Data Science Institute Professor, Lubar

College of Business

Co-Director, Northwestern Mutual Data Science Institute

Min Sook Park

Assistant Professor, Information Studies

Matthew Petering

Associate Professor, Industrial & Manufacturing Engineering

Department

Joseph Retzer

Teaching Faculty, Lubar College of Business

Aki Roberts

Associate Professor, Sociology

John Roberts

Professor, Sociology

Director of Graduate Studies

Paul Roebber

Distinguished Professor, School of Freshwater Sciences

Founder, Innovative Weather

Academic Program Director, Data Science Initiative

Mark Schwartz

Distinguished Professor, Geography - General

David Spade

Associate Professor, Mathematical Sciences - General

Akke Talsma

Associate Professor, College of Nursing

Jeb Willenbring

Professor, Mathematical Sciences - General

Chair for the Graduate Program

Dietmar Wolfram

Senior Associate Dean & Professor, Information Studies

Changshan Wu

Professor, Geography - General

Zeyun Yu

Professor, College of Engr. & Applied Sci.

Director, Big Data Analytics and Visualization Lab

Jun Zhang

Professor, College of Engr. & Applied Sci.

Chao Zhu

Professor, Mathematical Sciences - General

VI. RESOURCES

The program does not require any new facilities or new or additional course offerings. Courses

will be taught by current UWM faculty and staff or by qualified adjunct instructors, where

appropriate.

VII. BULLETIN COPY

Submit copy for the Graduate School Bulletin following the template provided by the Graduate

School.