Presentation to University Curriculum Committee (UCC) 2013 Proposal for a B.S. & M.S. degree in Data Science Data Science BS/MS Degree Proposal Presented

Presentation to

University Curriculum Committee (UCC)

2013

Proposal for a B.S. & M.S. degree in Data Science

Data Science BS/MS Degree Proposal

Presented by Gary Davis (MTH)

Presentation Outline

Program GoalsProgram HighlightsProgram BenefitsProgram FeasibilityDegree RequirementsLearning Outcomes

Data Science BS/MS Degree Proposal 2013

Proposal Overview


This proposal is to establish a new interdisciplinary Bachelor of Science and Master of Science degree program in Data Science (DSC). The major will provide undergraduate/graduate students with advanced education and training in the rapidly emerging fields of data analytics and discovery informatics, which integrates mathematics and computer science for the quantification and manipulation of information from a cognate area of application (e.g., science, engineering, business, sociology, healthcare, planning). Emphasis is placed on merging strong foundations in information theory, mathematics, statistics and computer science with current methodologies and tools to enable data-driven discovery, problem solving, and decision making.

Program Goals (BS)


1) Educate and train students to work in industry or academia as data scientists 2) Broaden and deepen the basic data science education in computer science,

mathematics, and statistics, with real-life data science projects in cognate disciplines, including Accounting, Biology, Chemistry, Decision & Information Sciences, Engineering, Finance, Marketing, Nursing, Physics, Political Science, and Sociology.

3) Expand education opportunities in rapidly growing areas of information science;

4) Offer state-of-the-art technology-based courses in data analysis, data mining, statistical modeling, and data visualization;

5) Prepare graduates with entry-level skills for managing, understanding, interpreting and communicating database and information needs of a wide variety of producers and consumers;

6) Increase enrollment in STEM disciplines; and,7) Stimulate and assist the development of computationally-focused options

within existing departments.

Program Goals (MS)


1) Meet the growing demand for high-level information systems/science skills;

2) Provide a path for individuals from diverse fields to rapidly transition to information science career paths;

3) Enable established information technology and computing professionals to upgrade their technical management and development skills;

4) Prepare graduates to apply data science techniques for knowledge discovery and dissemination to assist researchers or decision makers in achieving organizational objectives;

5) Establish stronger ties to alumni to enhance opportunities for continued learning and leadership;

6) Create a pool of innovators, entrepreneurs, business professionals who will lead the development of next generation information systems.

Program Highlights

• Mission focused• Interdisciplinary

• Multiple colleges and departments• Accessible and inclusive• Flexibility

• Contemporary• Innovative


Program Benefits


The proposed major will embody the mission of UMass Dartmouth through education, research, economic development, and public service.•It will prepare students of diverse backgrounds for success in technologically-oriented careers in the knowledge-based economy.•It will increase innovation and scientific advancement through research.•It will provide a pathway for women and men from diverse fields to rapidly transition to information science career paths.•It will prepare a citizenry capable of bringing insight to complex information in an ethical and socially responsible way.•It will support the needs of the business community in Massachusetts and the nation.•It will sustain the university's reputation for innovative academic programs and overall excellence in undergraduate, graduate and professional education.

Program Priority

2013Data Science BS/MS Degree Proposal

Technical Need


Workforce Need


Mass Technology Leadership Council, Big Data and Analytics: A Major Market Opportunity for Massachusetts (2012)

McKinsey Global Institute, Big Data: The Next Frontier for Innovation, Competition and Productivity (May 2011)

Program FeasibilityAbility to offer program:• Two main participating departments are MTH and CIS• 15+ faculty available; additional hires in progress• 1.5 FTE faculty needed to deliver 6 new DSC courses• No new faculty hires necessary to launch DSC program• Facilities and labs – High-performance computing cluster

at UMD and MGHPCC; Data and Visual Analytics Lab (under development); Ctr. for Scientific Computing & Visualization Research

• Software/equipment from grants/gifts/major fees• Library resources: ~$8K for additional journals• Student activities/recruitment/publicity from major fees


Degree Requirements (BS)


Coursework: 120 credit hours of coursework with at least 45 credits taken in the upper division•Core courses include mathematics (20 CHs), statistics (9 CHs), computer science (17 CHs), and data science (12 CHs).•Elective courses 12 CHs upper division•University Studies 30 CHs

GPA major ≥ 2.50GPA overall ≥ 2.00

Degree Requirements (MS)


Coursework: 30 credit hours of coursework•Core courses include mathematics/computing (6 CHs), and data science (6 CHs)•Elective courses (15 CHs)•Practicum (3 CHs)•24 CHs must be earned at the 500-level or above

GPA overall ≥ 3.00

Comprehensive examination on core competencies = pass

Academic progress: completion in 1.5 - 2 years (full-time study)

Admission Requirements (BS)


• A student who meets the University’s general eligibility requirements may apply to the BS program in Data Sciences.

• Established admission criteria apply: http://www.umassd.edu/admissions/

• DSC qualifications should be in top 10 percent of applicants with an aptitude for mathematics and computer science.

• Mathematics readiness is determined by the ACCUPLACER® test results.

• Articulation agreements are planned for transfer students to enter with up to 70 course credits.

Admission Requirements (MS)

Requirements are:•Baccalaureate degree from an accredited college or university•Undergraduate GPA ≥ 3.00 in relevant coursework•Proficiency in mathematics and computing•Minimum TOEFL score 550 (paper), 213 (CBE), 79 (Internet), if applicable

Up to 6 credits may be transferred into graduate programs at UMD


Learning Assessment


An ongoing process of quality control and outcomes assessment will contain the following elements.1)End of Course Evaluations2)Small Group Instructional Diagnosis3)Web Archive of the Student Projects4)Exit Interview and Survey5)Transcript Analysis6)Long-term Career Tracking

Program Assessment


Benchmarks of SuccessThe success of the entire program will be assessed against the following benchmarks:1)Meeting enrollment targets;2)Graduation rates (45% 6-yr UG; 80% 2-yr GR) and degrees awarded;3)Satisfaction of students with the program, measured by course evaluations and web-based exit surveys with graduating students (at least 85% satisfied or very satisfied);4)Success of graduates in pursuing advanced degrees, obtaining high-quality employment or advancing to higher positions within their present organization; and,5)Long-term professional success of the graduates, measured by 5-year alumni and employer surveys.



• Statistics oExploratory data analysisoStratified samplingoRegression, linear modelsoGoodness of fit of statistical modelsoAnalysis of varianceoDesign of experimentsoDigital signal processing

• Machine learning (quantitative analysis)• General programming ability

oPython and pandasoRoMATLAB, Maple, MathematicaoMapReduce/HadoopoHigh Performance Computing (e.g. via MATLAB)oDatabases: MySQL

• Data communication oData visualizationoWeb programming: HTML 5, CSS, php, javascript

Body of Knowledge (BS/MS)

Learning Outcomes (BS)


At the time of graduation, students will:•be able to understand and apply contemporary techniques for managing, mining, and analyzing big data across multiple disciplines;•be able to use computation and computational thinking to gain new knowledge and to solve real-world problems of high complexity;•have the ability to communicate their ideas and findings persuasively in written, oral and visual form and to work in a diverse team environment;•be prepared for graduate school or employment and have an appreciation for life-long learning;•have an appreciation for the professional, societal and ethical considerations of data collection and use.

Learning Outcomes (MS)


At the time of graduation, students will:•be able to understand and apply contemporary techniques for managing, mining, and analyzing big data across multiple disciplines;•be able to use computation and computational thinking to gain new knowledge and to solve real-world problems of high complexity;•have the ability to communicate their ideas and findings persuasively in written, oral and visual form and to work in a diverse team environment;•have a deep knowledge of computing and information systems applications, including network, database, security and privacy, and Web technologies;•be better prepared for career advancement in all areas of information science and technology;•be committed to continuous learning about emerging and innovative methods, technologies, and new ideas, and be able to bring them to bear to help others; and,•have an appreciation for the professional, societal and ethical considerations of data collection and use.

Program FAQsQ1. Are there similar programs elsewhere?


Bentley UniversityM.S. in Marketing AnalyticsBoston UniversityM.S in Computer Information SystemsUniversity of California, IrvineM.S. in InformaticsCarnegie Mellon UniversityM.S. in Information Systems ManagementM.S. in Information TechnologyPhD in Machine LearningCollege of CharlestonB.S. in Discovery InformaticsCornell UniversityM.Eng. Operations Research and Information EngineeringDePaul UniversityM.S. in Predictive AnalyticsDrexel UniversityB.S. in Information SystemsB.S. in Information TechnologyM.S. in Business AnalyticsGeorge Mason UniversityPhD in Computational Sciences and InformaticsB.S. in Computational and Data SciencesIndiana University-Purdue University Indianapolis School of InformaticsPhD in Informatics

UMass BostonGraduate Certificate in Database TechnologyUniversity of MaineM.S. in Information SystemsUniversity of MichiganB.S. in InformaticsB.S. in InformationNorth Carolina StateM.S. in AnalyticsNortheastern UniversityMaster of Professional Studies in InformaticsNorthwestern UniversityMaster of Science in AnalyticsMaster of Science in Predictive Analytics (Online Program)NYUM.S. in Information SystemsM.S. in Information Systems EngineeringM.S. in Business AnalyticsUniversity of PittsburghB.S. in Information ScienceM.S. in Information ScienceUniversity of San FranciscoM.S. in AnalyticsSyracuse University School of Information StudiesGraduate Certificate of Advanced Studies in Data ScienceStevens Institute’s Wesley J. Howe School of Technology ManagementMaster of Science in Business Intelligence and Analytics

Program FAQs (cont.)Q2. What is the current enrollment in the participating departments?


Fall 2012 Enrollment Data

College Dept BS MS PhD Total

CAS MTH 71 – – 71

COE CIS 177 47 – 224

Total 248 47 – 295

Program FAQs (cont.)Q3. What are enrollment projections?


# of Students Year 1



# of Students Year 4*

New Full Time 10 15 20 25

Continuing Full Time 0 7 25 35

New Part Time 0 0 0 0

Continuing Part Time 0 0 0 0

Totals 10 22 45 60

B.S. Degree M.S. Degree

B.S. Degree

M.S. Degree





New Full Time 5 7 10 10

Continuing Full Time 0 5 8 10

New Part Time 0 5 5 5

Continuing Part Time 0 0 5 10

Totals 5 17 28 35

*Reflects students graduating

Documents

Presentation to University Curriculum Committee (UCC) 2013 Proposal for a B.S. & M.S. degree in Data Science Data Science BS/MS Degree Proposal Presented