Course Advice
Students Considering a Major in Data Science
Data science is new and evolving; there are many important combinations of theoretical, applied, and field-specific knowledge that may provide a foundation for future work. If you are interested in a data science major, we recommend that you work with your advisor to choose a set of related courses that reflect your interests and priorities from the list of electives. Course combinations that focus on individual topics, disciplines, or domains are strongly recommended. We also strongly recommend substantial engagement with issues of ethics, which could be in one focused course or across multiple courses.
Students Considering Graduate School or a Career as a Data Scientist:
While there are many fields for which the combination of data analysis and computational tools may be valuable, we have particular recommendations for students seeking a future as a data scientist. We strongly recommend that you take both COMSC-335 Machine Learning and STAT-340 Applied Regression Methods. Ideally, at least one course should involve an extended project requiring the analysis of data. We also recommend that you contextualize your data science preparation in the content of a domain or area of study that is theoretically and empirically cohesive.
Course Offerings
DATA-113 Introduction to Data Science
Data scientists answer questions with scientific and social relevance using statistical theory and computation. We will discuss elementary topics in statistics and learn how to write code (in Python) to visualize data and perform simulations. We will use these tools to answer questions about real data sets. We will also explore ethical issues faced by data scientists today.
DATA-225 Topics in Data Science:
DATA-225AR Topics in Data Science 'Ethics and Artificial Intelligence'
Artificially intelligent technologies are prominent features of modern life -- as are ethical concerns about their programming and use. In this class we will use the tools of philosophy to explore and critically evaluate ethical issues raised by current and future AI technologies. Topics may include issues of privacy and transparency in online data collection, concerns about social justice in the use of algorithms in areas like hiring and criminal justice, and the goals of developing general versus special purpose AI. We will also look at ethics for AI: the nature of AI 'minds,' the possibility of creating more ethical AI systems, and when and if AIs themselves might deserve moral rights.
DATA-295 Independent Study
DATA-390 Data Science Capstone
The Capstone is a research seminar that empowers students to design and execute a significant data science research project. Through group review of journal articles and targeted lectures, students will develop a thorough understanding of each of the components of a successful research project including defining their research question, conducting a literature review, identifying an appropriate data set, designing and implementing a defensible methodology, and presenting and interpreting their results in text, tables, and figures. There will be frequent opportunities for students to present their work, and their capstone will culminate in a written report. Concurrently, students will read and discuss several case studies that address issues of ethics involved with the collection, treatment, and analysis of data.
DATA-395 Independent Study
DATA-395P Independent Study w/Practicum
Required Core Courses for the Data Science Major
Course List
Code |
Title |
Credits |
COMSC-151 | Introduction to Computational Problem Solving | 4 |
COMSC-205 | Data Structures | 4 |
COMSC-335 | Machine Learning | 4 |
MATH-211 | Linear Algebra | 4 |
PSYCH-326CP | Laboratory in Personality and Abnormal Psychology: 'Advanced Statistics in Clinical Psychology' | 4 |
STAT-140 | Introduction to the Ideas and Applications of Statistics | 4 |
STAT-242 | Intermediate Statistics | 4 |
STAT-340 | Applied Regression Methods | 4 |
Note: Majors need to take either COMSC-335 or STAT-340.
Elective Courses for the Data Science Major
Course List
Code |
Title |
Credits |
BIOL-223 | Ecology | 4 |
BIOL-234 | Biostatistics | 4 |
BIOL-321GE | Conference Course: 'Genomics and Bioinformatics' | 4 |
CHEM-291 | Scientific Illustration and Data Visualization | 4 |
CHEM-328 | From Lilliput to Brobdingnag: Bridging the Scales Between Science and Engineering | 4 |
CHEM-348 | Using Data Science to Find Hidden Chemical Rules | 4 |
COMSC-133DV | Data Visualization: Design and Perception | 4 |
COMSC-235 | Applications of Machine Learning | 4 |
COMSC-312 | Algorithms | 4 |
COMSC-334 | Artificial Intelligence | 4 |
COMSC-335 | Machine Learning | 4 |
COMSC-341NL | Topics: 'Natural Language Processing' | 4 |
COMSC-341TE | Topics: 'Text Technologies for Data Science' | 4 |
DATA-113 | Introduction to Data Science | 4 |
DATA-225AR | Topics in Data Science 'Ethics and Artificial Intelligence' | 4 |
DATA-390 | Data Science Capstone | 4 |
ECON-220 | Introduction to Econometrics | 4 |
ECON-320 | Econometrics | 4 |
EOS-299AR | Topic: 'Ethics and Artificial Intelligence' | 4 |
GEOG-205 | Mapping and Spatial Analysis | 4 |
GEOG-210 | GIS for the Social Sciences and Humanities | 4 |
MATH-339PT | Topics in Applied Mathematics: 'Optimization' | 4 |
MATH-339SP | Topics in Applied Mathematics: 'Stochastic Processes' | 4 |
MATH-342 | Probability | 4 |
PHIL-260AR | Topics in Applied Philosophy: 'Ethics and Artificial Intelligence' | 4 |
SOCI-216TX | Special Topics in Sociology: 'Text as Data I: From Qualitative to Quantitative Text Analysis' | 4 |
SOCI-316TX | Special Topics in Sociology: 'Text as Data II: Computational Text Analysis for the Social Sciences' | 4 |
STAT-244MP | Intermediate Topics in Statistics: 'Survey Sampling' | 4 |
STAT-244NF | Intermediate Topics in Statistics: 'Infectious Disease Modeling' | 4 |
STAT-244NP | Intermediate Topics in Statistics: 'Nonparametric Statistics' | 4 |
STAT-331 | Design of Experiments | 4 |
STAT-340 | Applied Regression Methods | 4 |
STAT-343 | Mathematical Statistics | 4 |
STAT-344TM | Seminar in Statistics and Scientific Research: 'Time Series Analysis' | 4 |
STAT-351 | Bayesian Statistics | 4 |