The University Senate of Michigan Technological University
Proposal 20-14
(Voting Units:
Academic)
“Proposal for a New Non-Departmental
Graduate Certificate in Data Science”
February 28, 2014
Contacts: Laura Brown (Computer Science), Mari W.
Buche (School of Business
& Economics), Gowtham S (Information
Technology Services), Timothy Havens
(Electrical & Computer Engineering/Computer
Science), Jacqueline Huntoon
(Graduate School), Saeid Nooshabadi (Electrical
& Computer
Engineering/Computer Science), and Allan
Struthers (Mathematics)
e-mail: datascience@mtu.edu
Executive Summary
This proposal describes a
plan for a new Graduate Certificate in Data Science. This program will augment
the proposal for a Master of Science (M.S.) in Data Science. Like its M.S.
counterpart the Graduate Certificate in Data in Science the has three main
objectives: i) to attract students from various disciplines who wish to learn
the basics of data analysis, data science, and computing tools; ii) to teach
students basic skills in communication and build their awareness of business
contexts; and iii) to provide students the opportunity to gain the basic skills
that give them the ability to analyze large data sets, including Big Data.
Our goal is to have all
the core data science courses and most approved data science
courses offered online by
2016, which we note would allow off-campus students to fully
complete the Graduate
Certificate in Data Sciences with online offerings.
1. Background
The proposed Graduate
Certificate is offered as subset of M.S. in Data Science and is
offered to science and
engineering graduates who wish to upgrade their qualification to
be able to work in a
profession with a primarily role to manage and analyze data.
2. Justification and Estimated Market
The program we are
proposing will significantly increase the number of data scientists that
Michigan Tech can offer
to the workforce. The Graduate Certificate program in Data
Science like its M.S.
counterpart will provide students with strong academic training in data
analysis in a range of
areas (e.g., physical sciences, geosciences, geoinformatics,
bioinformatics,
cheminformatics, environmental, social sciences, business and commerce)
while at the same time
introduce essential business acumen, communication and teamwork skills highly
valued by industry and government.
The proposed program
emphasizes data analytics from a general perspective, but the skills to be
learned are applicable to a diverse range of areas, including business
analytics, computer science and engineering, and informatics. To support the
interdisciplinary nature of the Data Science program, applications from
multiple areas will be included in the coursework.
The proposal Data Science program
is in line with Michigan Tech strategic plan1 to “be a
leader in creating
solutions for society's challenges through education and interdisciplinary
endeavors that advance
sustainable economic prosperity…”
3. Competitive Analysis
Established computer
science, business analytics, and statistics master’s degrees and
certificate programs
already exist, both in the U.S. and abroad, and provide specializations in data
mining and predictive analytics. However, despite interest and recognized need,
there are as yet only a few programs dedicated to data science in the U.S.
Further, the existing programs have been designed around business data with a
less domain-specific scientific focus. These master’s programs include
Northwestern’s new M.S. in Analytics, DePaul’s M.S. in Predictive Analytics,
University of San Francisco’s M.S. in Analytics, LSU’s M.S. in Analytics,
Rutgers’s Professional Science Master’s (PSM) of Business and Science in
Analytics, and NCSU’s M.S. in Analytics (also a PSM program).
Finally, there is
increased recognition by federal agencies that supporting Big Data research is
important. For example, the National Institutes of Health (NIH) director, Dr.
Francis Collins, recently convened a “Data and Informatics Working Group” that
made several key recommendations aimed at fostering NIH sponsored research in
Big Data. Other federal agencies have also signaled interest in Big Data
research, including National Science Foundation, DARPA, Department of Energy,
and Department of Defense.
____________________
1 STRATEGIC
PLAN https://www.banweb.mtu.edu/pls/owa/strategic_plan2.p_display
4. Detailed Description of Graduate Certificate in Data Science
i. Title:
Graduate Certificate in
Data Science
ii. Catalog description:
The non-departmental Data
Science program at Michigan Tech provides a foundation for the emerging field
of “Big Data” science, including the use of data mining, predictive analytics,
cloud computing, and business skills, with a domain specific specialization.
The main threads of analytic techniques, programming practice, domain
knowledge, business acumen, and communication skills are intertwined in this
program.
The Graduate Certificate
in Data Sciences provides the basic skills in data analytics, data
management, business and communication
skills. Entry into this program assumes basic
knowledge in statistical
and mathematical techniques, programming, and communications.
iii. Credits:
Graduate Certificate in
Data Science 15
credits (minimum)
iv. Course work:
In accordance with Senate
policy, the requirements for the interdisciplinary Graduate
Certificate in Data
Sciences are a minimum 15 credits of coursework, including the required
12 credits of core courses
and 3 credits of approved Data Science electives. All other
requirements are per
Senate proposals 11-10 and 4-11. Because this is an interdisciplinary
certificate, a maximum of
six credits can be earned at the 3000-4000 level.
Coursework Summary
Core courses for M.S. Data Science (12 credits):
The four required core 3-credit
courses focus on basic skills in data science analytics, data
mining, and business
analytics. These courses are:
● UN 5550 -
Introduction to Data Science (3 credits)2
● MA 4790 -
Predictive Modeling (3 credits)
● CS 4821 / MA 4795
- Data Mining (3 credits)
● BA 5200 -
Information Systems Management and Data Analytics (3 credits)3
___________________________________
2 New
course to be designed for Fall 2014; submitted to curriculum proposal (binder)
Fall 2013. This
course will be
administered by the Office of Dean of the Graduate School, and executed by Data
Science
faculty across the campus.
3 Revise
course BA 5200-Strategic IS Management; submitted to curriculum proposal
(binder) Fall 2013
Approved Data Science elective courses for M.S. Data Science (minimum of 3 credits):
The remaining 3 credits for the graduate certificate must be taken from the approved 3-credit Data Science elective courses that are
as
part of the
M.S. program in Data Science as
below:
● CS 5841 / EE 5841 -
Machine Learning (3 credits)4
● CS 5491 -
Cloud Computing (3 credits)5
● CS 5471 – Advanced Topics in Computer Security (3 credits)6
● MA 5781 -
Time Series Analysis and Forecasting (3 credits)7
● BA 5740 - Managing
Innovation & Technology (3 credits)
● PSY 5210 - Advanced Statistical Analysis and Design I (4 credits)
● FW 5083 -
Bioinformatics Programming and Skills (3 credits)8
Foundational Prerequisite Requirement:
It is expected that students seeking enrollment in this program will
have sufficient foundational
skills and aptitude in computer programming, statistical analysis, information systems and
databases. The required foundational skills may have been obtained through formal academic
qualifications, work
experience, or a combination. Students will be encouraged to develop
their foundational skills before coming to Michigan Tech to start the
graduate certificate program in Data Science. After taking the entrance assessment exam and evaluation of
the
student’s application, students will receive advice regarding their skill competence and may be required to take specific foundational courses (Appendix
I) as necessary to acquire the required level of foundational skills. As students matriculate in the program, their assigned
advisors will
continually monitor students’ progress to ensure that students are
given all the
necessary advice that they need to be successful in the
program. Appendix
I provides a list of
foundational courses.
v.Online delivery:
Our goal is to have all the
core data science courses and most approved data science
courses offered online by 2016, which we note would allow off-campus students to fully
complete the
Graduate Certificate in Data Sciences with online offerings. Note that BA 5200 - Information Systems Management and Business Analytics will be offered as an online course starting in 2014. Additionally, the approved Data Science courses, CS 5841 / EE 5841 -
Machine Learning and CS 5491 -
Cloud Computing, will
be
offered as online courses in 2016.
4 New course to be designed for Spring 2015; submitted to curriculum proposal (binder) Fall 2013
5 New course to be designed for Spring 2015; submitted to curriculum proposal (binder) Fall 2013
6 New course to be designed for Spring 2015; submitted to curriculum proposal (binder) Fall 2013
7 Graduate version of MA 4780, submitted to curriculum proposal (binder) Fall 2013, to be offered as a
split-level undergraduate/ graduate course. The graduate version of this course contains additional theoretical material and substantial project work.
8 Graduate version of FW 4099, submitted to curriculum proposal (binder) Fall 2013, to be offered as a
split-level undergraduate/ graduate course. The graduate version of this course contains additional theoretical material and substantial project work.