Data Science Minor
Bowers College of Computing and Information Science
Program Description
Offered university wide, the minor in Data Science equips students from any major with a solid understanding of the conceptual and methodological tools of data-driven discovery. Upon completing the minor, students will be ready to leverage competencies and skills to pursue careers in various fields and professions.
Program Requirements
The requirements to complete the minor balance the specific learning outcomes with flexibility and choice, with courses distributed across the participating colleges and disciplines, to ensure students can pragmatically complete the minor along with concurrently meeting major and distribution/elective requirements.
To Complete the Minor
- Six courses are required in total
- One course from the core statistics category. These are restricted to those courses for which a calculus-based understanding of probability can provide understanding in concepts such as maximum likelihood estimation.
- One course from the core computer programming category. This course might be either an introductory programming course or one of a select number of more advanced courses.
- Four courses from the courses listed under the following categories:
- Data Analysis
- Domain Expertise
- Big Data Ethics, Policy and Society
- Data Communication
- For the four categories, at least one course should be from each of three different categories, while the fourth can come from any category.
Important Information about Major/Minor Overlaps
Students may count a maximum of two courses toward both the Data Science minor and their own major’s core requirements, though they may count other courses they take for the minor toward their major’s elective requirements, provided their department approves.
1) CS Majors:
- You may count a maximum of two courses toward both the Data Science Minor and your CS core courses, CS electives, and/or CS practicum requirements for the CS major.
- You may, however, count other courses you take for the Data Science Minor toward your CS technical electives, external specialization, major-approved and/or advisor-approved elective coursework, but only if those courses meet the requirements for that category of elective.
2) Students who are majoring in a subject that requires an introductory programming course (such as CS 1110 Introduction to Computing: A Design and Development Perspective), must satisfy the “Core Computing” requirement with a more advanced programming course.
Given the overlap of INFO courses in the Data Science Minor and the Data Science Concentration in the Information Science Minor, students cannot declare both.
Data Science Minor Courses
Core Statistics
| Code | Title | Hours |
|---|---|---|
| ECE 3100 | Introduction to Probability and Inference for Random Signals and Systems | 4 |
| ENGRD 2700 | Eng Probability and Statistics: Modeling and Data Science | 4 |
| GOVT 4019 | 4 | |
| MATH 4710 | Basic Probability | 4 |
| MATH 4720 | Statistics | 4 |
| ORIE 3500 | Eng Probability and Statistics: Modeling and Data Science II | 4 |
| STSCI 3080 | Probability Models and Inference | 4 |
| STSCI 3110 | Applied Probability and Statistics | 4 |
| ECON 3130 | Probability and Statistics | 4 |
| STSCI 2200 | Statistics I | 4 |
Core Computing
| Code | Title | Hours |
|---|---|---|
| AEM 2820 | Introduction to Database Management Systems | 3 |
| AEM 2830 | VBA for Data Analysis and Business Modeling | 3 |
| AEM 2840 | Python Programming for Data Analysis and Business Modeling | 3 |
| AEM 2850 | R Programming for Business Analytics and Data Visualization | 3 |
| CS 1110 | Introduction to Computing: A Design and Development Perspective | 4 |
| CS 1112 | Introduction to Computing: An Engineering and Science Perspective | 4 |
| CS 3220 | Computational Mathematics for Computer Science | 3 |
| CS 4320 | Introduction to Database Systems | 3 |
| HADM 3740 | Fundamentals of Database Management and Data Analysis | 3 |
| ORIE 3120 | Practical Tools for Operations Research, Machine Learning and Data Science | 4 |
| STSCI 3040 | R Programming for Data Science | 4 |
| STSCI 4060 | Python Programming and its Applications in Statistics | 4 |
| STSCI 4520 | Statistical Computing | 4 |
Data Analysis
| Code | Title | Hours |
|---|---|---|
| AEM 3275 | Introduction to Machine Learning in Business | 3 |
| AEM 4120 | Computational Methods for Management and Economics | 3 |
| ASTRO 3334 | Data Analysis and Research Techniques in Astronomy | 3 |
| ASTRO 3340 | Symbolic and Numerical Computing | 4 |
| ASTRO 4523 | Modeling, Mining and Machine Learning in Astronomy | 3 |
| BEE 4310 | Environmental Statistics and Learning | 4 |
| CHEME 5660 | Financial Data, Markets, and Mayhem for Scientists and Engineers | 3 |
| CS 3780 | Introduction to Machine Learning | 4 |
| CS 4787 | Principles of Large-Scale Machine Learning Systems | 4 |
| CS 4850 | Probability, Vectors, and Matrices in Computing | 4 |
| ECE 4110 | Random Signals in Communications and Signal Processing | 4 |
| ECE 4200 | Fundamentals of Machine Learning | 4 |
| ECE 4250 | Digital Signal Processing and Statistical Inference | 4 |
| ECON 3120 | Applied Econometrics | 4 |
| ENGRD 2720 | Data Science for Engineers | 4 |
| HADM 4010 | Data Driven Analytics | 3 |
| HADM 4750 | Machine Learning for Business and Hospitality Applications | 1.5 |
| HD 2930 | Introduction to Data Science for Social Scientists | 3 |
| HD 2940 | Data Science for Social Scientists II | 3 |
| HD 4760 | Quantitative Methods II | 3 |
| INFO 2950 | Introduction to Data Science | 4 |
| INFO 2951 | Introduction to Data Science with R | 4 |
| INFO 3300 | Visual Data Analytics for the Web | 3 |
| INFO 3370 | Studying Social Inequality Using Data Science | 3 |
| INFO 3950 | Data Analytics for Information Science | 3 |
| MATH 2310 | Linear Algebra for Data Science (if taken before FA24, not accepted) | 4 |
| ORIE 4580 | Simulation Modeling and Analysis | 4 |
| ORIE 4740 | Statistical Data Mining I | 4 |
| ORIE 4741 | ||
| ORIE 4820 | Data-Driven Decision Modeling and Analysis | 3 |
| PSYCH 4750 | 3 | |
| PSYCH 4760 | Quantitative Methods II | 3 |
| PUBPOL 3100 | Multiple Regression Analysis | 4 |
| STSCI 4060 | Python Programming and its Applications in Statistics | 4 |
| STSCI 4100 | Multivariate Analysis | 4 |
| STSCI 4110 | Categorical Data | 3 |
| STSCI 3740 | Data Mining and Machine Learning | 4 |
| STSCI 4780 | Bayesian Data Analysis: Principles and Practice | 4 |
Big Data Ethics, Policy & Society
| Code | Title | Hours |
|---|---|---|
| ALS 1210 | Data Democratization | 3 |
| COMM 4242 | ||
| DSOC 2120 | ||
| DSOC 4060 | ||
| ENGL 3778 | Free Speech, Censorship, and the Age of Global Media | 4 |
| ENGRG 3605 | Ethics of Computing and Artificial Intelligence Technologies | 3 |
| GOVT 3999 | How Do You Know That? | 4 |
| INFO 1200 | Information Ethics, Law, and Policy | 3 |
| INFO 1260 | Choices and Consequences in Computing | 3 |
| INFO 3200 | Technology, Behavior and Society | 3 |
| INFO 3370 | Studying Social Inequality Using Data Science | 3 |
| INFO 4240 | Designing Technology for Social Impact | 4 |
| INFO 4250 | Surveillance and Privacy | 3 |
| INFO 4270 | 3 | |
| INFO 4505 | Computing and Global Development | 3 |
| INFO 4561 | Evaluation and Society | 3 |
| NBA 4920 | AI for Business Applications | 1.5-3 |
| PUBPOL 2070 | Big Data for Big Policy Problems | 4 |
| PUBPOL 2130 | Data and the State: How Governments See People and Places | 4 |
| PUBPOL 3520 | Economic and Policy Implications of Artificial Intelligence | 3 |
| PUBPOL 4230 | ||
| PUBPOL 4540 | Collaborative Modeling Methods for Policy and Program Evaluation | 3 |
| STS 3440 | Data Science and Society Lab | 3 |
| STS 3561 | Computing Cultures | 4 |
| STS 3940 | 3 | |
| STSCI 3600 & STSCI 4850 | Integrated Ethics in Data Science and Data Science Consulting | 2 |
Data Communication
| Code | Title | Hours |
|---|---|---|
| COGST 3420 | Human Perception: Application to Computer Graphics, Art, and Visual Display | 3 |
| COMM 3010 | Writing and Producing the Narrative for Digital Media | 3 |
| COMM 3150 | Organizational Communication: Theory and Practice | 3 |
| COMM 3350 | ||
| COMM 3189 | Taking America's Pulse: Creating and Conducting a National Opinion Poll | 3-4 |
| COMM 4200 | ||
| COMM 4360 | Communication Networks and Social Capital | 3 |
| COMM 4860 | Risk Communication | 3 |
| INFO 3312 | Data Communication | 3 |
| INFO 3950 | Data Analytics for Information Science | 3 |
| INFO 4310 | Interactive Information Visualization | 3 |
| SOC 3580 | Big Data on the Social World | 3 |
Domain Expertise
| Code | Title | Hours |
|---|---|---|
| AEM 2770 | Excursions in Computational Sustainability | 3 |
| AEM 3100 | Business Statistics | 3 |
| AEM 4060 | Risk Simulation and Monte Carlo Methods | 3 |
| AEM 4110 | Introduction to Econometrics | 3 |
| AEM 4225 | Systems and Analytics in Accounting | 3 |
| AEM 4435 | Data Driven Marketing | 1.5 |
| AEM 4620 | Digital Innovation in Media Markets & Creative Industries | 3 |
| AEM 4660 | Business Simulation | 1.5 |
| ASTRO 3310 | Planetary Image Processing with MATLAB | 3 |
| BIOCB 4381 | Biomedical Data Mining and Modeling | 3 |
| BIOCB 4830 | Quantitative Genomics and Genetics | 4 |
| BIOCB 4840 | Computational Genetics and Genomics | 4 |
| BIOEE 3550 | Data Analysis and Visualization in Ecology and Environmental Science | 3 |
| BIOEE 3611 | Field Ecology | 3 |
| BIOEE 3620 | ||
| BIOEE 4940 | Special Topics in Ecology and Evolutionary Biology | 1-6 |
| BIOMG 4810 | Population Genetics | 4 |
| BIOMG 4870 | Human Genomics | 3 |
| BIONB 3300 | Introduction to Computational Neuroscience | 3-4 |
| BIONB 4220 | Modeling Behavioral Evolution | 4 |
| BIONB 4380 | Topics in Computational Methods for Neurobiology and Behavior | 3 |
| BTRY 4820 | ||
| CHEM 4810 | Computational Methods in Chemistry | 4 |
| COGST 3140 | Computational Psychology | 3 |
| CRP 4080 | Introduction to Geographic Information Systems (GIS) | 4 |
| CS 4300 | Language and Information | 3 |
| CS 4740 | Natural Language Processing | 4 |
| DSOC 3140 | ||
| EAS 3450 | Environmental Geophysics | 3 |
| ECON 3120 | Applied Econometrics | 4 |
| ECON 3140 | Econometrics | 4 |
| ECON 4110 | 3 | |
| ECON 4660 | Behavioral Economics | 4 |
| ENTOM 3030 | Applied Statistics: Biological Experiments in Practice | 4 |
| GOVT 3282 | Data Science Applications in Political and Social Research | 4 |
| HADM 4050 | Revenue Management | 3 |
| HADM 4770 | Advanced Business Modeling | 2 |
| INFO 3140 | Computational Psychology | 3 |
| INFO 3350 | Text Mining History and Literature | 3 |
| INFO 4100 | Learning Analytics | 3 |
| IFNO 4555 | ||
| ILRHR 4664 | Talent Analytics | 3 |
| ILROB 4710 | Social Science Research Methods | 3 |
| NS 4300 | Proteins, Transcripts, and Metabolism: Big Data in Molecular Nutrition | 3 |
| NTRES 3100 | Applied Population Ecology | 3 |
| NTRES 3500 | ||
| NTRES 4100 | Advanced Conservation Biology | 4 |
| ORIE 2380 | 3 | |
| ORIE 4120 | Inventory, Operations, and Supply Chain Management: Models and Optimization | 3 |
| ORIE 4126 | Principles of Supply Chain Management | 4 |
| ORIE 4132 | ||
| ORIE 4154 | Revenue Optimization and Marketplace Design | 3 |
| ORIE 4630 | Operations Research Tools for Financial Engineering | 4 |
| ORIE 4656 | Extreme Values in Finance | 3 |
| ORIE 4742 | Info Theory, Probabilistic Modeling, and Deep Learning with Scientific and Financial Apps | 3 |
| PLSCS 4110 | ||
| PLSCS 4200 | ||
| PLSCI 4290 | Remote Sensing and Modeling for Ecosystems | 3 |
| PLSCS 4650 | ||
| PUBPOL 3120 | Research Design and Methods of Social Research | 3 |
| PUBPOL 3130 | Behavioral Economics and Public Policy | 3 |
| PUBPOL 3280 | Fundamentals of Population Health | 3 |
| PUBPOL 3400 | The Economics of Consumer Policy | 3 |
| PUBPOL 3550 | Economics of Education | 3 |
| PUBPOL 3600 | Economics of Crime | 3 |
| PUBPOL 3670 | Economics and Environmental Policy | 3 |
| PUBPOL 3780 | Global Comparative Health Care Systems | 3 |
| PUBPOL 3850 | ||
| PUBPOL 4080 | Demographic Techniques | 3 |
| PUBPOL 4101 | Causal Reasoning and Policy Evaluation I | 3 |
| PUBPOL 4110 | Pollution, Climate Change, and Health | 3 |
| STS 4040 | Digital Due Process Clinic | 4 |
Questions about the minor should be directed to: Julia Aquadro (jra269@cornell.edu), Assistant Director of Undergraduate Advising.