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Programs, Certificates and Courses

Degree Programs

These are degree programs at UD with large Data Science component to them.

Department: Interdisciplinary
Graduate Degree(s): MS in Bioinformatics & Computational Biology, PSM in Bioinformatics, PhD in Bioinformatics Data Science
Contact: Karen Hoober, Assistant Director, Graduate Education & Outreach and Amelia Harrison, Academic Advisor

This program is an interdisciplinary program that offers multiple degree options. It is administered through the Department of Computer & Information Sciences and coordinated by the Center for Bioinformatics & Computational Biology (CBCB). The scientific curriculum is supported with the research strength, education resources, bioinformatics infrastructure, and Affiliated Faculty from ten participating Departments across the Colleges of Arts & Sciences, Engineering, Agriculture & Natural Resources, and Earth, Ocean & Environment, as well as the Delaware Biotechnology Institute and Data Science Institute. Whether their background is life sciences or computational/mathematical sciences, students, full-time or part-time, will gain core competency for job opportunities in the very rapidly growing field of bioinformatics.

Business Analytics

Department: Business Administration (MBA)
College: Alfred Lerner College of Business & Economics
Graduate Degree(s): MBA Major in Business Analytics
Contact: Director, Admissions & Recruitment: Patrick Cahill and Admissions Specialist: Bishakha Choudhuri

The Lerner MBA is designed to allow you to build a degree that fits your career goals. At the center of the program are the business core courses that give you a rock-solid foundation in business management knowledge and techniques across essential business functions. Then, based on your goals, you choose an elective courses option. With a major in Business Analytics students will gain the knowledge to inform business decisions by integrating data science, business strategy and management science.

Business Analytics and Information Management
Department: Accounting and MIS
College: Alfred Lerner College of Business & Economics
Graduate Degree(s): MS in Business Analytics and Information Management
Contact: Director: Andrea Everard and Academic Program Coordinator: Sarah Dix

The Lerner MS in Business Analytics and Information Management allows you to build a degree that fits your career goals. The flexible curriculum enables students to choose a business analytics focus, an information management focus or a blend of the two. The MS in Business Analytics and Information Management produces students who possess the combination of technical and management skills needed to bring about the effective deployment and administration of information technology to achieve business success in today’s highly competitive global environment.


Department: Electrical & Computer Engineering
Graduate Degree(s): MS in Cybersecurity 
Contact: Elizabeth Mestro and/or ece-info@udel.edu

Ensuring the security of the world’s and our own nation’s computers, systems, and networks is a key national security challenge.  Thus, establishing high-quality Cybersecurity educational programs is a top national priority as well as a regional imperative since trained Cybersecurity graduates are of critical importance to several large employer groups in this region.

The Cybersecurity master’s program is structured to enable professionals to gain advanced training in this field.  Unlike other programs that are solely focused on IT security, this program emphasizes design of secure software and systems, security analytics, and secure business systems.  It will train individuals that have a traditional background in engineering, computer science, information systems, or related fields to have strong security skills enabling them to develop new secure systems and/or software, to exploit analytics for security purposes, or to develop and manage secure business systems.  Thus graduates of this program will be skilled in the latest theories and practices required to address the most challenging cybersecurity issues facing the world today.

Data Science

Department: Interdisciplinary/Graduate College
Graduate Degree(s): MS in Data Science
Contact: msds-director@udel.edu

The interdisciplinary Master of Science in Data Science (MSDS) offers combined 4+1 Bachelors and MSDS programs that allow students to complete both the Bachelor’s degree from a variety of departments and the MSDS in a total of five years of full-time study. The undergraduate degree options include those from the Departments of Mathematical Sciences and of Physics and Astronomy in the College of Arts and Sciences; and the Departments of Computer and Information Sciences, of Electrical and Computer Engineering, and of Mechanical Engineering in the College of Engineering.  This program combines a flexible set of core requirements in probability and statistics, databases and data mining, machine learning, mathematics and computation, and ethics with electives in a wide range of application areas offered by departments across campus. Graduates receive strong foundations as well as hands-on experiences that open a wide range of career possibilities.

Department: Economics
Graduate Degree(s): PhD in Economics, MS Economics and Applied Econometrics
Contact: Director Sabrin Beg and Academic Program Coordinator Kelly Chan

Our doctorate in Economics focuses on developing applied research skills that are increasingly in demand in consulting, business, government, and academia. Because of the small class sizes, students receive the personal attention of the department’s highly qualified faculty. The PhD program emphasizes applied, policy-oriented economics and the development of strong econometric skills. Fields of specialization include development economics, industrial organization, labor economics, behavioral economics and household finance. The PhD in Economics is a STEM-designated degree program.

The MS in Economics and Applied Econometrics is a STEM-designated degree program. In today’s job market, economists with quantitative skills and experience in empirical research are in high demand. Our economy is increasingly data-driven, requiring workers who are skilled in analyzing and interpreting economic data to make decisions about national and global markets and economic
policy. This program teaches students to apply economic analysis to any situation while expanding opportunities to turn theoretical economic models into useful, practical tools for economic policymaking. With its strong emphasis on the quantitative skills needed to be successful, this MS degree, students are prepared to work in private industry, government, or academia in the US or

Educational Statistics
College: College of Education and Human Development
Graduate Degree(s): Ph.D. in Educational Statistics and Research Methods
Contact: Ken Shores (Program Coordinator)

The Ph.D. in Educational Statistics and Research Methods (ESRM) prepares students interested in education data science, research methods, statistics, causal inference, psychometrics, and evaluation to develop, critically evaluate, and properly use sophisticated quantitative and mixed methodologies to solve important problems in education.

Electrical & Computer Engineering

College: Electrical & Computer Engineering
Graduate Degree(s): MS and PhD in Electrical and Computer Engineering

Undergraduate Degree(s): Bachelor in Electrical Engineering, Computer Engineering, or Cybersecurity Engineering; Electrical Engineering/Data Science 4+1 (BEE/MS), Computer Engineering/Data Science 4+1 (BCE/MS)

Contact: Elizabeth Mestro and/or ece-info@udel.edu

Electrical and Computer Engineering are central to the technologies transforming society – information, security, robotics, energy and sustainability, and biology and medicine – providing the intellectual and technological bridge between the cyber and physical worlds.
The ECE Master’s and PhD programs are designed to broaden student’s electrical and computer engineering foundation knowledge while allowing them to research a variety of topics. Our students specialize in research areas including nanoelectronics and photonics, RF engineering, embedded systems and integrated circuits, hardware and software design, smart grid and energy systems, machine learning and large-scale data analysis, cybersecurity, high performance computing, quantum information and engineering, signal processing and imaging systems, and communication systems.

Undergraduate programs in Electrical, Computer, or Cybersecurity Engineering prepare students for careers in data science through foundational courses and technical electives that build theoretical understanding and hands-on experience in designing computational and electronic technology (hardware and software systems) that are used to sense, store, process, communicate, and analyze data. The courses are taught by experts in cybersecurity, artificial intelligence, autonomous control, data mining, imaging, information theory, optimization, and pattern recognition with applications in astronomy, biomedicine, defense, natural language processing, neuroscience, remote sensing, and robotics.

College: College of Health Sciences
Graduate Degree(s): Master of Public Health (MPH) in Epidemiology and PhD in Epidemiology
Contact: Lauren Camphausen, Academic Program Manager

The Master of Public Health (MPH) in Epidemiology is designed to prepare students for a career in public health in either applied (e.g., local, state or federal public health agencies) or research settings. By providing students with a comprehensive foundation of population health principles, epidemiological methods and biostatistics, and study design, the MPH in Epidemiology will ensure students are proficient in the skills needed to successfully enter the public health workforce.

The PhD in Epidemiology provides students with advanced training in epidemiological methods and prepares them for careers in research, teaching, and applied public health. The program is designed to support students with some experience in public health who seek additional training related to research methods and their application to population health. Sample areas of focus include cancer, cardiovascular disease, and injury epidemiology, among others.

Financial Services Analytics
Department: Institute for Financial Services Analytics (IFSA)
College: Alfred Lerner College of Business & Economics
Graduate Degree(s): Ph.D. in Financial Services Analytics (FSAN)
Contact: Program Director: Bintong Chen and Academic Program Coordinator:  Kelly Chan

Financial services analytics is the science of quantitative models and technologies designed for the financial services industry. It offers improvements in risk management, customer service, customized product offerings and business operation efficiency. The financial services analytics (FSAN) program at the University of Delaware is the first of its kind, developing fundamental FSAN theories, creating new data-driven decision-making tools and training researchers and professionals. The interdisciplinary program brings data analytics methods and non-traditional data sources to bear on issues important to the financial services industry, which differentiates it from programs in finance or financial engineering.

Geospatial Data Science

Department: Geography
College: College of Earth, Ocean, & Environment
Graduate Degree(s): PhD and MS in Geography, PhD in Climatology
Contact: Kyle Davis, Program Director

We have a growing faculty in Geospatial Data Science specialized in GIScience, Remote Sensing, Machine Learning, Big Data Analytics and Modeling, with applications in Land Change Science, Human Dimensions of Climate Change, Sustainability, and Climatology. The department also has strength in regional and large-scale climate modeling, weather forecasting, atmospheric observation, ecohydrology, political ecology, and critical geography. Funding may be available.

Hospitality Business Analytics
Department: Department of Hospitality and Sport Business Management and Institute for Financial Services Analytics (IFSA)
College: Alfred Lerner College of Business & Economics
Graduate Degree(s): Ph.D. in Hospitality Business Analytics
Contact: Graduate Director: Timothy Webb and Administrative Assistant III: Jen Riegner

The mission of the Ph.D. in hospitality business analytics program is to provide advanced training to students in data science as it relates to the hospitality industry. The goal is to prepare students for highly demanding academic and research careers in top‐ranked institutions. Our faculty conduct in-depth research in various areas of study that apply to hospitality business analytics, such as revenue management, digital marketing, finance, customer experience management and human resources management. The program emphasizes analytics, which is possible because our faculty has access to the large amounts of data being generated by information and communication technologies in the industry.

Interdisciplinary Neuroscience
Department: Interdisciplinary
College: Graduate College
Graduate Degree(s): Ph.D. in Interdisciplinary Neuroscience
Contact: Program Director: John Jeka and Graduate Services Coordinator: Wendy Feller

Contemporary neuroscience is an interdisciplinary field that studies the nervous system to understand the biological bases of behavior, cognition, subjective experience, psychiatric or neurological disease, and the brain’s computational processes, networks and functions. The idea of neuroscience as a dedicated and multidisciplinary branch of biology that synergistically combines physiology, anatomy, chemistry, physics, mathematical modeling, engineering, psychology and rehabilitation has resulted in a flourishing field.

The interdisciplinary neuroscience graduate (ING) program at the University of Delaware is designed to develop a unified atmosphere to expose students to the exciting developments in brain function, providing interdisciplinary training to current and future graduate students and prepare them for a research-oriented career in academics or industry.

Department: Applied Economics and Statistics
Graduate Degree(s): MS in Statistics and Applied Statistics (online)
Contact: Erma Wolpert

The program in Statistics leads to the Master of Science degree and offers students the perspectives and skills necessary to understand and work as a statistician in various sectors of the economy (business, manufacturing, pharmaceuticals, or government sectors). Also, a strong intermediate level of training is offered so that students may continue graduate work and obtain the PhD degree. The department has ready access to various state-of-the-art computing and library resources. We provide a generous financial aid package to qualified candidates. The Statistics program also has an internship program for interested students. The intern program, a cooperative effort of the Statistics Program at the University of Delaware, trains students by a combination of formal university graduate courses and “hands on” application in an industrial setting. The objective of the internship is to introduce the student to the “art” aspects of Applied Statistics to complement the theoretical foundations learned in the classroom. Delaware’s many chemical, pharmaceutical and industrial companies provide a unique place in which to use the intern concept because of the problem-solving nature of their work, and the availability of experienced statisticians to guide intern work. The online Applied Statistics program features an applied research project.

Water Science and Policy

Department: Interdisciplinary
Graduate Degree(s): Ph.D. with a water science concentration, Ph.D. with a water policy concentration, and Master of Science with thesis
Contact:  Professor and Director Rodrigo Vargas and Graduate Services Coordinator Wendy Feller

By choosing to study Water Science & Policy at the University of Delaware, you will be embarking on an exciting intellectual journey that will challenge you to synthesize knowledge from a number of different fields. No matter what aspect of water you choose as your research focus, you’ll be encouraged to look at how it intertwines with other natural and human aspects of water quality and quantity.


These are certificates at UD that are Data Science related.

Applied Research Methods

Department: Interdisciplinary
Certificate: Applied Research Methods Graduate Certificate
Contact: grad@udel.edu

This certificate is intended to prepare students in advanced research methods, primarily for the purposes of program and policy evaluation, but also for research studies and projects.

Artificial Intelligence

Department: Artificial Intelligence Center of Excellence
Certificate(s): Artificial Intelligence
Contacts: Co-Directors Sunita Chandrasekaran and Kathleen McCoy and Program Contact Chiamesha Carey

Artificial Intelligence is a rapidly evolving field that has been integrated into many facets of our daily lives, economy and education. AI uses various techniques, such as machine learning, to learn from data to make decisions or predictions that would otherwise require human intellect. It can also analyze large amounts of data, recognize patterns and learn from its experiences to improve its performance over time.

Skilled professionals in AI who understand how to build and train these systems are highly sought-after by many industries. A graduate certificate in AI can open the doors to a wide range of career opportunities and provide a competitive edge in areas such as healthcare, technology, finance and more.


Department: Interdisciplinary
Certificate(s): Graduate Certificates in Bioinformatics and Applied Bioinformatics (online)
Contact: Karen Hoober, Assistant Director, Graduate Education & Outreach and Amelia Harrison, Academic Advisor

Business Analytics

Department: Business Administration (MBA)
Certificate(s): Graduate Certificate Business Analytics 
Contact: mbaprogram@udel.edu

Where data science meets business strategy. The demand for professionals who understand and utilize big data has never been greater. Business analytics experts ensure decisions and actions are data driven and shape the future of business in real-time. This graduate certificate program allows working professionals to gain advanced knowledge and skills in the field of business analytics. Students take the same courses offered in the Lerner MBA and become proficient in leveraging data to make decisions, generate insights, optimize outcomes and predict future results.

Computational Science and Engineering

Department: Interdisciplinary
Certificate(s): Computational Science and Engineering
Contact: math-questions@udel.edu

The philosophy of the program is that we increase the capabilities and understanding of the student in a broad range of areas utilizing floating point or symbolic computation for solving medium to large scale problems in computational mathematics, science and engineering.

This is an interdisciplinary program currently involving seven departments and two colleges (Arts & Science and Engineering). The post-baccalaureate Certificate in Computational Science and Engineering may be completed with non-degree graduate status or as part of a graduate degree program. Students in this certificate program may thus have full- or part-time status.

Computing and Data Science for Soft Materials

Department: Graduate College
Certificate(s): Computing and Data Science for Soft Materials
Contacts: Director, Arthi Jayaraman and Coordinator, Jenn Johnston

This interdisciplinary graduate Certificate in Computing and Data Science for Soft Materials prepares students to use high performance computing and data science to discover, innovate, and engineer new synthetic and biologically relevant soft (specifically polymeric) materials with tailored properties and function.  The 9-credit curriculum and professional training activities are designed to provide graduate students convergent and interdisciplinary technical training in soft materials modeling, simulations, experiments, computing, and data analytics, supplemented with close and regular interactions with mentors from relevant industries, national labs, and members in academia. The training elements, the timing and order of the elements—is chosen deliberately to have a logical flow and progression starting from a strong disciplinary foundation to incrementally infusing interdisciplinary training through convergent research and coursework combined with development and practice of technical and broad communication skills through teamwork, leadership, and peer-mentoring experiences. The integrated technical and professional training elements will prepare the graduate students to be career-ready for multiple career paths academic, non-profit, and private sectors.


Department: Electrical & Computer Engineering
Certificate: Graduate Certificate in Cybersecurity
Contact: Elizabeth Mestro and/or ece-info@udel.edu

Ensuring the security of the world’s and our own nation’s computers, systems, and networks is a key national security challenge.  Thus, establishing high-quality Cybersecurity educational programs is a top national priority as well as a regional imperative since trained Cybersecurity graduates are of critical importance to several large employer groups in this region.

The Department of Electrical and Computer Engineering at the University of Delaware offers five (5) graduate Certificates in the broader area of Cybersecurity:

  • Certificate in Cybersecurity (Foundations)
  • Secure Systems Certificate (Concentration)
  • Secure Software Certificate (Concentration)
  • Security Management Certificate (Concentration)
  • Security Analytics Certificate (Concentration)


Department: College of Health Sciences
Certificate: Graduate Certificate in Epidemiology

Contact:  Certificate Director Amy Nelson and/or mph-info@udel.edu

The Graduate Certificate in Epidemiology is a 12-credit program specifically designed for working professionals and those interested in exploring Epidemiology at the graduate level. The Certificate curriculum emphasizes practical, applied skills in epidemiological methods and basic biostatistics. All courses have been specially designed and developed for delivery online. The certificate can be completed in 1 year of part-time study or in addition to another graduate degree program.

Geographic Information Science (GIS)

Department: Geography and Spatial Studies
Certificate(s): Geographic Information Science
Contacts: Director, Kyle Davis and Program Contact, Sue Biddle

Skills in geographic information science and geospatial data analysis offer students market-ready tools for turning data into informed decision-making. The GIS Certificate (in-person) and Geospatial Data Science Certificate (online) teach students to process and interpret data from around the world, preparing them to address issues like climate change, environmental degradation, population growth, transportation planning, disaster management and more.
These certificate programs are designed for working professionals aspiring to leadership positions. Whether you’re seeking to improve your technical skill set or looking to advance your geographical problem-solving and spatial thinking, the Department of Geography and Spatial Sciences has a variety of GIS courses, certificates, and graduate degree programs (MA, MS, and PhD) that can help you meet your goals.  

Large Scale Data Analytics

Department: Electrical and Computer Engineering
Certificate(s): Large Scale Data Analytics
Contacts: ece-info@udel.edu


Machine Learning

Department: Electrical and Computer Engineering
Certificate(s): Machine Learning Foundations Certificate
Contacts: ece-info@udel.edu

Minerals, Materials and Society

College: College of Earth, Ocean, and Environment (CEOE)
Certificate(s): Graduate Certificate in Minerals, Materials and Society (MMS)
Contact: Saleem Ali, MMS Academic Director

The Minerals, Materials and Society (MMS) program is one of the first programs of its kind in the United States to offer a for-credit graduate certificate aimed at industry, government and civil society professionals working across mineral and extractive supply chains. The program approaches the topic from an interdisciplinary and industrial ecology perspective with attention to key skills needed to evaluate the environmental and social impacts of the sector. We are committed to a science-based approach to the topic but with respect for multiple normative perspectives from industry, government and civil society.


Department: Applied Economics and Statistics
Certificate(s): Statistics Certificate
Contact: Erma Wolpert

The Graduate Statistics Certificate is designed for graduate students across the University who desire to gain additional proficiency and knowledge in statistical methods to augment their disciplinary graduate studies. The certificate helps students burnish their quantitative credentials for the job market and gain necessary skills to complete their graduate thesis or dissertation work. All required courses focus on applied content, but students may substitute courses that most closely align with their needs.

This unique opportunity greatly enhances UD graduate students’ skill set without pursuing an additional, full degree. Students build quantitative and analytical skills in statistics and data science that not only helps during your graduate studies, but in your post-UD career. SAS, R and other statistical programming languages launch our students into a higher level of data analysis.

The certificate builds upon your current disciplinary graduate studies. This value-added piece to your resume allows you to stand out to future employers. Our faculty ensure that these valuable statistical analysis skills apply directly to your chosen discipline of study. In addition, many courses are available online, adding flexibility to your schedule.

Urban Data Science

Department: Joseph R. Biden, Jr. School of Public Policy & Administration (udel.edu)
Certificate(s): Urban Data Science
Contacts: Greg Dobler and bidenschool@udel.edu.

The 4-course certificate in urban data science (UDS) will provide students with the skills to apply data science techniques and methodologies to pressing problems in urban policy and administration, planning, and the emerging science of cities.

The UDS certificate is closely aligned with​​ the M.A. in urban affairs and public policy in the Biden School, which treats the urban environment as the fundamental construct and prepares students to address critical societal issues across multiple spatial scales and disciplines. The UDS certificate enhances that approach as it conceptualizes cities as complex systems with three fundamental components—the human, natural, and built environments—whose interactions can be explored and understood through spatial and temporal quantitative and qualitative data.


These are Data Science related courses taught by the DSI Resident Faculty, Affiliated Faculty or members of the DSI Faculty Council.

Note that course numbers ending in 67 is reserved for new courses so many different courses from the same department will have this same course number. Please double check that the course title matches when doing course registration.

ACCT602 – Big Data Technologies

ACCT604 – Database Design and Implementation

BINF601 – Introduction to Data Sciences

BINF610 – Applied Machine Learning

BINF640 – Databases for Bioinformatics

BINF644 – Bioinformatics

BINF667 – Seminar: Big Data in Social, Behavioral, and Health Sciences

BINF667-018 – Electronic Health Records (EHR) Data Science

BINF685/CISC685 – Modeling and simulation for bioinformatics systems

BMEG802 – Advanced Biomedical Experiment Design & Analysis

BUAD621 – Decision Analytics and Visualization

CIEG642 – Advanced Data Analysis

CISC367 – Introduction to Data Science

CISC436/636 – Computational Biology and Bioinformatics

CISC467/667-010 – Cloud Computing

CISC467/667-011 – Computing for Social Good

CISC474 – Advanced Web Technologies

CISC481/681 – Artificial Intelligence

CISC482/682 – Introduction to Human-Computer Interaction

CISC483 – Introduction to Data Mining

CISC484/684 – Introduction to Machine Learning

CISC637 – Database Systems

CISC689 – Artificial Intelligence: Introduction to Network Science

CISC849 – Advanced Topics in Computer Applications: Game Theory for Distributed Systems

CISC849 – Advanced Topics in Computer Applications: Intro to Educational Data Mining

CISC867/ELEG867-015 – Seminar: Elective Course: Computing and data science for soft materials innovation & discovery

CISC889 – Advanced Topics in AI: Deep Learning

CISC889-011 – Human-Centered AI

COMM306 – Digital Technology and Politics

CPEG/ELEG652 – Principles of Parallel Computer Architectures

CPEG467/667 – Computational & Data-Intensive Research Platforms & Applications

CPEG657 – Search and Data Mining

CRJU467-011 – Data Science for Criminal Justice

ECON306 – Introduction to Econometrics

ECON422 – Econometric Methods and Models I

ECON423 – Econometric Methods and Models II

ECON622 – Applied Econometrics I

ECON822 – Econometric Theory I

ECON823 – Econometric Theory II

ECON824 – Econometrics of Cross-Section and Panel Data

EDUC865 – Measurement Theory

EDUC867 – Survey Design for the Social Sciences

EDUC873 – Multilevel Models in Education

EGGG367 – Data Science I

ELEG305 – Signals and Systems

ELEG405/ELEG605 – Engineering Machine Learning Systems

ELEG491 – Ethics and Impacts of Engineering

ELEG601 – Convex Optimzation

ELEG631 – Digital Signal Processing

ELEG668 – Detection and Estimation

ELEG815/FSAN815 – Statistical Learning

ELEG817/CISC817/FSAN817 – Large scale machine learning

ENWC417/617 – Quantitative Ecology

EPID603 – Biostatistics for Health Sciences I

EPID604 – Introduction to Epidemiologic Data Analysis in SAS

EPID605 – Epidemiology Methods I

EPID610 – Epidemiology Methods II

EPID613 – Biostatistics for Health Sciences II

EPID614 – Biostatistics for Health Sciences III

EPID621 – Methods in Field Epidemiology

EPID631 – Analyzing Epidemiologic Data Using R

FINC/FSAN841 – Financial Services Markets

FINC/FSAN842 – Financial Services Risk Analytics

FINC430 – Fintech and Data Science for Finance

FSAN820 – Foundation of Optimization

FSAN830 – Business Process Management Innov

GEOG/MAST481/681 – Remote Sensing of Environment

GEOG/PHYS/SPPA167 – Foundations of Data Science for Everyone

GEOG271 – Introduction to Geographic Data Analysis

GEOG367/UAPP367/ELEG367/CISC367/PHYS367 – Geospatial Data Science

GEOG372 – Introduction to GIS

GEOG405 – Computer Programming for Environmental Research

GEOG472/686 – Cartography: Art & Science of Mapping Data

GEOG480/680 – Know Your Satellites

GEOG604 – GIS in Environmental Research

GEOG605010 – Computer Programing for Environmental Research

GEOG667 – Spatial Data Analysis & Modeling

GEOG670 – Geographic Information Systems and Science

GEOG671 – Advanced Geographic Information Systems

GEOG681 – Remote Sensing of Environment

GEOL427/627 – Introduction to Geological Remote Sensing

HOSP448 – Data Analytics in the Hospitality Industry

HOSP890 – Hospitality Business Analytics

MAST629 C/L CIEG629 – Marine Ecosystem Modeling

MAST638 – Machine Learning for Marine Science

MAST686 – Remote Sensing Seminar (1 credit)

MATH219 – Data Science I

MATH419 – Data Science II

MATH612 – Computational Method for Equation Solving and Function Minimization

MATH637 – Mathematical Techniques in Data Science

MATH667 – Topological Data Analysis

MISY467 – Machine Learning for Business

MISY615 – Enterprise Architecture: Digitally Transforming Business

MISY636 – Unstructured Data Analytics

MISY640 – Project Management and Costing

MISY641 – Data Mining for Business Analytics

MISY650 – Security and Control

MISY655 – Ethics in Technology Management

MISY665 – Introduction to Cybersecurity

MISY667 – Introduction to Python

MISY675 – Dashboard Design & Storytelling

NURS844/HLTH844 – Population Healthcare Informatics

PHIL655 – Ethics in Data Science & Artificial Intelligence

PHYS467 – Data Science for Scientists

PHYS667 – Machine Learning for Time Series Analysis

PHYS667 – Computer Vision for the Physical Sciences

POSC815 – Introduction to Statistical Analysis for Political Science

POSC817 – Statistical Analysis for Political Science II

SOCI301 – Introduction to Sociological Research

SOCI614 – Advanced Data Analysis

SOCI625 – Advanced Social Statistics

SPPA667-011 – Seminar: Urban Evidence Based Policy

SPPA721 – Data Science Tools for Evidence-based Policy

SPPA800 – Research Design and Data Analysis

STAT601010 – Probability Theory for Operations Research and Statistics

STAT602 – Mathematical Statistics

STAT603 – Statistical Computing and Optimization

STAT608 – Statistical Research Methods

STAT611 – Linear Regression

STAT612 – Advanced Regression Techniques

STAT613 – Applied Multivariate Statistics

STAT617 – Multivariate Methods and Statistical Learning

STAT619 – Time Series Analysis

STAT621 – Survival Analysis

STAT622 – Statistical Network Analysis

STAT631 – Introduction to Python

STAT632 – Introduction to JMP Software

STAT634 – Introduction to R

STAT656 – Biostatistics

STAT675 – Logistic Regression

UAPP667 – Machine Learning for Public Policy

Our Mission

The Institute aims to accelerate research in data science, serving as a nucleating effort to catalyze interdisciplinary research collaborations across fields impacting our society.