Graduate Certificate in Applied Data Science: Approved Courses

The Graduate Certificate requires three graduate-level courses. All three courses must be taken for a letter grade and completed with a grade of B or higher.*

At least one of these courses must be taken outside the student's home school or department.

* Note: any courses taken towards the Graduate Certificate in Applied Data Science in Spring 2020, Fall 2020, or Spring 2021 may be taken on an S/U basis instead of a letter grade and must be completed with an S grade (an S grade is a B– or higher). This exception is only approved for Spring 2020, Fall 2020, and Spring 2021 due to COVID-19; courses taken in any other semester require a letter grade of B or higher.

1. Introductory Data Science Course

One required synthetic introduction to data science class.

• INFO 201 Research Design and Applications for Data & Analysis
• DATASCI 201 Research Design and Applications for Data and Analysis (MIDS & MICS students only)

Students who have officially declared their intention to pursue the certificate in CalCentral may be eligible for priority enrollment into INFO 201. Please follow these instructions to declare the certificate.

2. Course in Analytical Methods and Techniques of Data Science

Students must take one course from this list.

• BIO ENG 245 Introduction to Machine Learning in Computational Biology (4 units)
• COMPSCI C200A Principles and Techniques of Data Science (4 units)
• COMPSCI C281A Statistical Learning Theory (3 units)
• COMPSCI 289A Introduction to Machine Learning (4 units)
• CYBER 207. Applied Machine Learning for Cybersecurity (3 units) (MIDS & MICS students only)
• DATA C200 Principles and Techniques of Data Science (4 units)
• DATA 200S Principles and Techniques of Data Science (3 units)
• DATASCI 207. Applied Machine Learning (3 units) (MIDS & MICS students only)
• EDUC 244 Data Mining and Analytics (3 units)
• INFO 251 Applied Machine Learning (3 units)
• INFO 258 Data Engineering (4 units)
• INFO 271B Quantitative Research Methods for Information Systems and Management (3 units)
• PB HLTH 241 Intermediate Biostatistics for Public Health (4 units)
• PB HLTH W241 Intermediate Biostatistics for Public Health (4 units)
• PSYCH 208 Methods in Computational Modeling for Cognitive Science (3 units)
• SOCIOL 273L Computational Social Science (3 units)
• STAT C200C Principles and Techniques of Data Science (4 units)
• STAT C241A Statistical Learning Theory (3 units)

3. Elective

A domain-specific data science course or a second methods course.

Students must take one course from this list or a second methods course from the list under (2), above.

All classes are 3 units except where noted otherwise.

• A,RESEC 213 Applied Econometrics (4 units)
• CIV ENG C263H Human Mobility and Network Science
• CIV ENG 263N Scalable Spatial Analytics
• CIV ENG 291D Data-driven Control Methods for Civil Engineering
• COMPSCI C267 Applications of Parallel Computers
• COMPSCI 286A Introduction to Database Systems (4 units)
• COMPSCI 281B Advanced Topics in Machine Learning and Decision Making
• COMPSCI 288 Natural Language Processing (4 units)
• COMPSCI 294 Special Topics (Spring 2022, section 150: “Machine Learning Meets Biology” topic only)
• CY PLAN 204C Introduction to GIS and City Planning (4 units)
• CY PLAN 255 Urban Informatics and Visualization
• CY PLAN 257 Data Science for Human Mobility and Socio-technical Systems (4 units)
• CY PLAN C257H Human Mobility and Network Science
• DEVP 229 Quantitative Methods and Impact Evaluation
• DATASCI 209 Data Visualization (MIDS & MICS students only)
• DATASCI 241 Experiments and Causal Inference (MIDS & MICS students only)
• DATASCI 266 Natural Language Processing with Deep Learning (MIDS & MICS students only)
• EDUC 275B Data Analysis in Educational Research II (4 units)
• EDUC 275G Hierarchical and Longitudinal Modeling
• EDUC 276E Research Design and Methods for Program and Policy Eval
• EECS 227AT Optimization Models in Engineering (4 units)
• EL ENG 227BT Convex Optimization (4 units)
• EL ENG C227C Convex Optimization and Approximation
• EL ENG C227T Introduction to Convex Optimization (4 units)
• ENGIN C233 Applications of Parallel Computers
• ESPM 215 Hierarchical Statistical Modeling in Envir Science (2 units)
• ESPM 288 Reproducible and Collaborative Data Science
• EWMBA 200S Data and Decisions (2 units)
• EWMBA 247 Topics in Operations and Information Technology Management (2 units) (Fall 2022, Fall 2023, & Fall 2024 topic “Descriptive and Predictive Data Mining” only)
• EWMBA 263 Marketing Analytics
• GEOG 249 Spatiotemporal Data Analysis in the Climate Sciences
• GEOG 279 Statistics and Multivariate Data Analysis for Research
• GEOG 282 GIS: Applications in Geographical Research (4 units)
• GEOG 285 Topics in Earth System Remote Sensing
• IND ENG 242 Applications in Data Analysis
• IND ENG C227A Introduction to Convex Optimization (4 units)
• IND ENG C227B Convex Optimization and Approximation
• IND ENG 262A Mathematical Programming I (4 units)
• IND ENG 262B Mathematical Programming II
• IND ENG 264 Computational Optimization
• IND ENG 265 Learning and Optimization
• IND ENG 266 Network Flows and Graphs
• IND ENG 269 Integer Programming and Combinatorial Optimization
• INFO 213 Introduction to User Experience Design (4 units)
• INFO 241 Experiments and Causal Inference
• INFO 247 Information Visualization and Presentation (4 units)
• INFO 256 Applied Natural Language Processing
• INFO 259 Natural Language Processing (4 units)
• INFO 288 Big Data and Development
• INFO 290T Special Topics in Technology (2–3 units) (“Biosensory Computing” topic only)
• JOURN 221 Introduction to Data Visualization
• LD ARCH 289 Applied Remote Sensing
• LINGUIS 252 Computational Linguistics
• LINGUIS 290L Additional Seminar on Special Topics to Be Announced (Fall 2020 only)
• MAT SCI 215 Computational Materials Science
• MBA 200S Data and Decisions (2 units)
• MBA 247 Topics in Operations and Information Technology Management (2 units) (Fall 2022 & Fall 2023, topic “Descriptive and Predictive Data Mining” only)
• MBA 263 Marketing Analytics
• MBA 296 Special Topics in Business Administration (2 units) (Fall 2019 & 2020, section 7B, & Spring 2023, Section 8: “Data Science Applications in Finance and Accounting” only)
• MEC ENG 249 Machine Learning Tools for Modeling Energy Transport and Conversion Processes
• MFE 230P Financial Data Science (2 units)
• PB HLTH 231A Analytic Methods for Health Policy and Management
• PB HLTH C240A Intro to Modern Biostatistical Theory and Practice (4 units)
• PB HLTH C240B Survival Analysis and Causality (4 units)
• PB HLTH C240C Comp Statistics with Apps in Biology and Medicine (4 units)
• PB HLTH C240D Comp Statistics with Apps in Biology and Medicine II (4 units)
• PB HLTH C242C Longitudinal Data Analysis (4 units)
• PB HLTH 244 Big Data: A Public Health Perspective (3-4 unit)
• PB HLTH W251B Data Visualization for Public Health (2 units)
• PB HLTH 251C Causal Inference and Meta-Analysis in Epidemiology (2 units)
• PB HLTH W252 Epidemiologic Analysis (4 units)
• PHYSICS 288. Bayesian Data Analysis and Machine Learning for Physical Sciences (4 units)
• POL SCI C236A The Statistics of Causal Inference in the Social Science (4 units)
• POL SCI C236B Quantitative Methodology in the Social Sciences (4 units)
• POL SCI 231B Quantitative Analysis in Political Research (4 units)
• POL SCI 239T Intro to Computational Tools & Techniques for Soc Sci Research
• PSYCH 206 Structural Equation Modeling
• PSYCH 207 Person-Specific Data Analysis
• PUB POL 246 Data Science for Public Policy (4 units)
• PUB POL 249 Statistics for Program Evaluation (4 units)
• PUB POL 275 Spatial Data and Analysis (4 units)
• PUB POL 279 Research Design and Data Collection for Public Policy Analysis
• PUB POL 288 Risk and Optimization Models for Policy (4 units)
• PUB POL 290 Special Topics in Public Policy (“Data Science for Public Policy” or “Quantitative Methods and Evaluation” topics only)
• SOCIOL C271D Quantitative/Statistical Research Methods in Social Sciences
• SOCIOL 273M Computational Social Science
• SPANISH 209 Seminar in Hispanic Linguistics (4 units) (Spring 2019, “Quantitative Methods in (Spanish) (Socio)Linguistics” only)
• STAT 215A Applied Statistics and Machine Learning (4 units)
• STAT 215B Statistical Models: Theory and Application (4 units)
• STAT 238 Bayesian Statistics
• STAT C239A The Statistics of Causal Inference in the Social Science (4 units)
• STAT C239B Quantitative Methodology in the Social Sciences (4 units)
• STAT 241B Advanced Topics in Machine Learning and Decision Making
• STAT 243 Introduction to Statistical Computing (4 units)
• STAT 244 Statistical Computing (4 units)
• STAT C245A Intro to Modern Biostatistical Theory and Practice (4 units)
• STAT C245B Survival Analysis and Causality (4 units)
• STAT C245C Comp Statistics with Apps in Biology and Medicine (4 units)
• STAT C245D Comp Statistics with Apps in Biology and Medicine II (4 units)
• STAT C247C Longitudinal Data Analysis (4 units)
• STAT 248 Analysis of Time Series (4 units)
• STAT 256 Causal Inference (4 units)
• STAT 259 Reproducible and Collaborative Statistical Data Science (4 units)
• STAT C261 Quantitative/Statistical Research Methods in Social Sciences
• VIS SCI 265 Neural Computation