Data Science

Courses

See the course catalog for complete course descriptions.

Minor in Data Science: Five courses
  • One course in Statistics from:
    • MAT52-114 Introduction to Statistics
      This course provides students in the social and biological sciences with the skills necessary to perform elementary statistical analysis. Topics include descriptive measures, probability, sampling theory, random variables, binomial and normal distributions, estimation and hypothesis testing, analysis of variance, regression and correlation. This course may not be used for the Mathematics major or minor. Contributes to Data Science and Health Studies (Fall, Spring) (NS)
    • MAT52-574 Probability and Mathematical Statistics
      This course is a calculus-based, mathematical introduction to the fundamental principles of probability theory and applications. Topics include combinatorial analysis used in computing probabilities, the axioms and properties of probability, conditional probability, independence of events, discrete and continuous random variables, the standard distributions, expected value and variance, joint distributions, distributions of a function of a random variable, and sampling distributions. Also included are theoretical results such as Bayes' Theorem, Central Limit Theorem, Law of Large Numbers, the Empirical Rule, Hypothesis Testing and Confidence intervals at least for a single mean and a single proportion. Prerequisite: Mathematics 52-264. Contributes to Data Science. (Spring) (NS)
  • One course in Computer Science from:
    • CSC54-144 Explorations in Computing
      This course is an introduction to the discipline of computer science with an emphasis on applications in the liberal arts. Topics include basic programming constructs, basic data structures, algorithmic computation, selection, iteration, interactive user interfaces, abstraction and reasoning about computer programs. This is an introductory course intended for humanities, social science and fine arts majors. May not be used for the Computer Science major or minor. Cannot be taken after successful completion of Computer Science 54-184, 54-284, or 54-454 without departmental approval. Contributes to Data Science. (Spring) (NS)
    • CSC54-184 Computer Science I
      This is the standard first course in computer programming in an object-oriented style. It is primarily intended for students pursuing a major or minor in computer science, mathematics or other disciplines in the natural sciences. Topics include primitive types and operations, assignment, conditional execution, iteration, arrays, classes, methods, recursion, encapsulation, type extension, inheritance and reasoning about programs in Java. The course includes a laboratory component designed to explore applications and to enhance conceptualization. Contributes to Data Science. (Fall, Spring) (NS)
  • Two courses in the application of data science from:

    (Note: The following two half-semester classes must both be taken to satisfy one of the two courses requirement.)

    • BIO50-222 Methods in Ecology and Evolutionary Biology (3-3; Half Semester)
      This lecture/laboratory course is a foundation-building course that contains instruction on reading the primary literature in ecology and evolutionary biology, conducting literature searches, designing experiments, writing scientific papers, using quantitative methods, exercising critical thinking skills for data analyses, creating graphs, and developing specific laboratory and field research skills for ecology and evolutionary biology. Contributes to Data Science. Prerequisite: Biology 50-123/121 and 50-133/131, and Mathematics 52-114. (Fall and Spring) (NSL) (WA)
    AND
    • BIO50-232 Methods in Cellular/Molecular Biology (3-3; Half-Semester)
      This lecture/laboratory course is a foundation-building course that contains instruction on reading the primary literature in cellular/molecular biology, conducting literature searches, designing experiments, writing scientific papers, using quantitative methods, exercising critical thinking skills for data analyses, creating graphs and developing specific laboratory skills for cellular/molecular biology. Contributes to Data Science. Prerequisites: Biology 50-123/121 and 50-133/131. Chemistry 51-103 is required, but Chemistry 51-203 is recommended. (Fall and Spring) (NSL) (WA)
    • BIO50-474 Genetics, Genomics, and Medicine
      An exploration of human phenotype, including Mendelian, polygenic and environmental influences, using approaches ranging from family studies and evolutionary medicine to population genomics. The lab will focus on bioinformatic resources in genetics, genomics, and medicine. Contributes to Data Science. Prerequisite: Biology 50-123/121, Biology 50-133/131, and either Biology 50-222, Kinesiology 48-214, or Psychology 33-204. (NSL)
    • BUS30-424 Strategic Marketing
      This course utilizes business cases and discussions to illustrate fundamental business issues which include: defining an organization's business and mission, developing strategies for business growth, and devising strategies to contend with unanticipated business changes. The course emphasizes the role of marketing in all of these strategic decisions and in delivering value to the end consumer. Students analyze a variety of issues including new product launch decisions, advertising campaigns, ethical dilemmas related to business operations, and global expansion strategies. Contributes to Data Science, Design Thinking and Health Studies. Prerequisite: Business 30-214. (ScS)
    • BUS30-434 Digital Marketing
      This course covers the fundamentals of digital marketing. Students learn how to apply and adapt traditional marketing strategies to an electronic domain (e.g., understanding the Internet for distribution). The classes and readings introduce students to search engine optimization (SEO), website management, and e-mail campaign strategies. The course also includes discussions of the ethical issues surrounding and related to e-marketing including privacy and psychological well-being. The latter part of the class is focused on social media. This includes analysis of social media metrics and user sentiment. Contributes to Data Science. Prerequisite: Business 30-214. (ScS)
    • CSC54-414 Operations Research
      Formulation and solution of problems with management, economics, engineering and science applications using modeling, optimization techniques, and simulation. Topics include linear and integer programming, simplex method, duality, sensitivity analysis, branch and bound algorithm, transportation and assignment problems, network optimization, and problem solving using optimization software. Also Mathematics 52-414 and Business 30-414. Prerequisites: Mathematics 52-164 (Modern Calculus I), and either Business 30-474 (Finance) or Mathematics 52-674 (Linear Algebra), or permission of the instructor. Contributes to Data Science.
    • CSC54-514 Database Management
      An introduction to the theory and practice of database management systems. Topics include database terminology, the entity-relationship model, the relational model, normalization, querying databases using SQL, and exploration of other database technologies. The course includes a laboratory component designed to explore applications and to enhance conceptualization. Prerequisite: Computer Science 54-284 or permission of instructor. (NS)
    • ECO31-314 Econometrics
      Quantitative and qualitative research methods for economic problems. Research design, data collection and statistical analysis of cross-sectional and time series data are covered. A major research paper and a weekly computer lab are required. Prerequisites: Economics 31-224, 31-234 and Mathematics 52-114, or permission of instructor. Contributes to Data Science. (Fall) (WA) (ScS)
    • ECO31-634 Data Analytics
      An introduction to commonly used techniques in data analytics. The application of statistical analysis and data visualization to draw conclusions about data. Applications will include sampling, forecasting, extrapolation, and regression analysis. Contributes to Data Science. Prerequisites: Mathematics 52-114, and Mathematics 52-164 or Business 30-154, or permission of instructor. (ScS)
    • ENV49-204 Environmental GIS
      This course introduces students to the practice and theory of Geographic Information Systems (GIS) as a method for analysis of the environment. Students will examine the fundamentals of GIS and GIS applications, learning the concepts needed to effectively manipulate, query, analyze, and visualize spatial-based data. At the end of the semester students should feel comfortable applying GIS to a range of environmental issues, and have a solid understanding of the procedures and data necessary to conduct geographical analysis. Contributes to Data Science. (NSL)
    • KIN48-214 Research Methods in Kinesiolog
      This course covers the basic concepts of research methods used in the discipline of kinesiology. It is designed to help students think critically, to give students hands-on experiences with research design, data analysis and interpretation, and to report results to a professional audience. Prerequisite: Mathematics 52-114 or permission of instructor. (Fall and Spring) (NS) (WA)
    • PSC32-394 Research Methods in Political Science
      This course will introduce students to basic approaches to research design and analysis in political science. Over the course of the semester, we will design research topics and questions, develop empirically testable hypotheses, collect relevant data, and apply basic qualitative and quantitative data analysis techniques. Topics covered in this course will span all areas of politics, international relations, and political institutions. Pre-requisites: Political Science 32-114 or 32-144 or permission of instructor. Contributes to Data Science and Design Thinking. (ScS)
    • PSC32-444 Political Psychology
      This course analyzes political issues from a psychological perspective to assess the role that the political brain plays in shaping our institutions, public policy, and political behavior. The course also introduces students to research methods typical in the study of political behavior. Contributes to Data Science and Psychology. Pre-requisites: Political Science 32-114 or Psychology 33-104. (ScS)
    • PSC32-534 Public Opinion: Fact Or Fantasy?
      This course explores the factors that shape public opinion, from question wording to socialization to the media and beyond. How do people arrive at their political opinions and how can we be sure that these opinions are grounded in facts and rational understanding of the issues at hand? We investigate the malleability of public opinion and under what conditions government officials should (and do) take it under consideration when making political decisions. We also conduct our own public opinion research, paying attention to the methods used to assess individual opinions and how these methods shape our understanding of what the public wants. Contributes to Data Science. Prerequisites: Political Science 32-364 or 32-384, or permission of instructor. (ScS) (American Politics)
    • PSY33-204 Survey of Research Methods
      This course introduces students to a variety of research methods in psychology, including experimental and non-experimental designs. Topics include literature review, hypothesis formation, psychological measurement, sampling, design, statistical analysis, ethics, and scientific writing in APA style. This course (with no lab) covers the basic methodological background necessary for upper-level psychology courses but does not involve project-based research. It is recommended for (a) psychology majors pursuing non-psychology careers or who prefer an internship capstone rather than a research capstone, (b) psychology minors, and (c) non-psychology majors preparing to take the MCAT. Prerequisites: Psychology 33-104 and Mathematics 52-114, minimum grades of C required. Contributes to Data Science. (Spring) (WA) (ScS)
    • PSY33-214 Inquiry-Based Research Methods
      This course gives students in-depth experience with the research methods used in psychology, including experimental and non-experimental designs. Topics include literature review, hypothesis formation, psychological measurement, sampling, statistical analysis, ethics, and scientific writing in APA style. This course (which includes a required 1-credit lab; 33-211) involves intense project-based original research, and serves as good preparation for later independent research (capstone research or graduate school). This course is recommended for (a) psychology majors who prefer a research capstone over an internship capstone, and (b) students considering applying to graduate school in psychology. Co-requisite: Concurrent registration in 33-211, with the same professor, is required. You must register for lecture and lab with matching section numbers (e.g. 33-214-01 & 33-211-01). Prerequisites: Psychology 33-104 and Mathematics 52-114, minimum grades of C required. Contributes to Data Science. (Fall, Spring) (WA) (ScS) Not appropriate for first-year students.
    • SOC34-314 Research Methods
      This course acquaints majors and minors in sociology with the procedures for gathering and analyzing sociological data. Students are required to participate in lab sessions as a part of the course. Contributes to Data Science. Prerequisite: Sociology 34-114 or 34-124, Mathematics 52-114, and sociology major or permission of the instructor. (Fall) (WA) (ScS)
    • SOC34-364 Sociology of Work
      This course investigates the institution of work from a sociological perspective. Topics include: a brief history of the evolution of work, work patterns prevalent in the United States, and modern-day concerns with employment inequality by race, gender, class, sexual orientation and the work-life balance. Students are required to attend SPSS lab sessions (during normal class time). They will perform quantitative analyses using employment discrimination complaint data and write a paper based on the results. Contributes to Business, Data Science, and Race and Ethnicity Studies. (ScS)
  • One course in the social issues concerning data science from:
    • EDU40-124 Foundations & Curriculum of American Sch
      An examination of the educational history of the United States and the changes in curriculum that have developed through the years. The course will focus on the different philosophies of curriculum organization, as well as the scope and sequences of subjects in elementary and secondary schools. Included in the course of study are considerations of multicultural education, legal and ethical issues concerning the teaching profession, and the responsibilities of the teacher in today's society. (ScS) (WA) (SPRING)
    • HIS16-264 History of Modern Europe
      This course surveys the history of Europe from the late eighteenth century revolutions through the creation and expansion of the European Union. We explore social, political, intellectual, and cultural developments, paying particular attention to reform movements and revolutions. The course tracks shifting ideas of gender, race, and class, as well as examining Europe's role in the world. Contributes to Data Science, Feminist Studies, and International Studies. (Biennially) (H)
    • HIS16-544 History of Human Rights
      This course places contemporary human rights debates within a long historical context, from Classical and religious traditions, through the Enlightenment, the abolition of slavery, and the growth of socialism, to the signing of the Universal Declaration of Human Rights in 1948, the movements for decolonization, and the present day. We track the gradual expansion of notions of rights, as well as changing understandings of who counts as human. The course includes discussions of political rights, social and economic rights, women's rights, minority rights, cultural rights, and environmental rights (among many others). Contributes to Data Science, Feminist Studies, and International Studies. (Biennially) (H) (SJ)
    • PHI18-244 Business As an Ethos
      This course examines key developments and debates, begun in the late 19th and early 20th centuries, regarding the seeming decline of the liberal ideal of free markets of competitive individuals. The rise of large corporations, global financial institutions, management as a form of scientific control, etc. underwrote a cultural transformation in which business became not only an academic discipline but also an ethos - the fundamental character and spirit of a culture. What that ethos entails, what resistances it has inspired, and what new forms it takes in today's neoliberal era, will be the subject of historical and theoretical inquiry. Contributes to Business and Economics. (H)
    • PSC32-564 Modern Political Theory
      This course explores experience of modernity and the concept of enlightenment, as well as disenchantment and alienation. We analyze Romantic and Modernist responses to the problems and possibilities enabled by modernity, with a focus on the practice of politics in everyday life. This course will focus on sensory perception, aesthetics, and the political implications of how we experience the world, comparing and connecting how these themes play out in 19th century American Transcendentalist versions of Romanticism and 20th century continental versions of Modernism. Contributes to Race and Ethnicity Studies. Prerequisite: Political Science 32-364 or permission of instructor. (ScS) (Political theory)
    • SOC34-214 Criminology
      This course examines the sociological foundations of crime including factors such as residential segregation, economic inequality, and masculinity. Some attention will also be devoted to American and international perspectives on criminal justice. Contributes to Data Science. (ScS) (SJ)

To complete the minor, students will complete a final assessment administered by the Faculty Coordinator.

No more than two courses can be selected from any one academic discipline (refer to course numbers’ 3 letter prefixes to identify disciplines). Internships cannot count towards the minor.