Electives
There are two categories of electives in our curriculum:
- Computer science, mathematics, statistics, and engineering electives. This page is a list of courses which can used for this category. Please note that in addition to the courses listed here, Core Biomedical Informatics Courses (BIOMEDIN 202, 212, 214, 215) taken in excess of the minimum requirement for the degree (two for PhD students, four for MS students) can be used for this category as well.
- Unrestricted electives. These can be any graduate-level courses at Stanford at or above the 100 level (subject to degree-specific limits).
Note that a course not on this list is not an allowable elective. If you want to add a course to this list, send email to BMI Student Services for consideration. Your particular course plan still needs to be approved by your academic advisor and the BMI Exec. Not all subsets of the following list are acceptable, for example, in the case of significant overlap between courses. Also, to find a course on this list, you may need to look under its cross-listed course id.
APPPHYS 215: Numerical Methods for Physicists and Engineers
APPPHYS 217: Estimation and Control Methods for Applied Physics
APPPHYS 223: Stochastic and Nonlinear Dynamics (BIO 223)
APPPHYS 223B: Nonlinear Dynamics: This Side of Chaos
APPPHYS 293: Theoretical Neuroscience
APPPHYS 315: Methods in Computational Biology
APPPHYS 345: Advanced Numerical Methods for Data Analysis and Simulation
BIO 223: Stochastic and Nonlinear Dynamics (APPPHYS 223)
BIOC 223: Open Problems in Biology
BIODS 205: Bioinformatics for Stem Cell and Cancer Biology
BIODS 215: Topics in Biomedical Data Science: Large-scale inference
BIODS220: Artificial Intelligence in Healthcare (CS271, BIOMEDIN220)
BIODS 237: Deep Learning in Genomics and Biomedicine (BIOMEDIN 273B, CS 273B, GENE 236)
BIODS 239: Introduction to Analysis of RNA Sequence Data (BIOC 239)
BIODS 253: Software Engineering for Scientists
BIODS 260A,B,C: Workshop in Biostatistics (STATS 260A,B,C)
BIOE 115: Computational Modeling of Microbial Communities (MI 245)
BIOE 210: Systems Biology (BIOE 101)
BIOE 285: Computational Modeling in the Cardiovascular System (CME 285, ME 285)
BIOE 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOMEDIN 279, BIOPHYS 279, CME 279, CS 279)
BIOE 291: Principles and Practices of Optogenetics
BIOE 300B: Engineering Concepts Applied to Physiology
BIOE301E: Computational Protein Modeling Laboratory
BIOE331: Protein Engineering
BIOE 332: Large-Scale Neural Modeling
BIOE 334: Engineering Principles in Molecular Biology
BIOMEDIN 219: Mathematical Models and Medical Decisions
BIOMEDIN 220: Artificial Intelligence in Healthcare (BIODS 220, CS 271)
BIOMEDIN 221: Machine Learning Approaches for Data Fusion in Biomedicine
BIOMEDIN 222: Cloud Computing for Biology and Healthcare (CS 273C, GENE 222)
BIOMEDIN 224 does NOT count towards this category
BIOMEDIN 226: Digital Health Practicum in a Health Care Delivery System
BIOMEDIN 233: Intermediate Biostatistics: Analysis of Discrete Data (EPI 261, STATS 261)
BIOMEDIN 245: Statistical and Machine Learning Methods for Genomics (BIO 268, CS 373, GENE 245, STATS 345)
BIOMEDIN 248: Clinical Trial Design in the Age of Precision Medicine and Health (BIODS 248, BIODS 248P, STATS 248)
BIOMEDIN 248B: Causal Inference in Clinical Trials and Observational Study (II)
BIOMEDIN 251: Outcomes Analysis (HRP 252, MED 252)
BIOMEDIN 262: Computational Genomics (CS 262)
BIOMEDIN 273A: The Human Genome Source Code (CS 273A, DBIO 273A)
BIOMEDIN 273B: Deep Learning in Genomics and Biomedicine (BIODS 237, CS 273B, GENE 236)
BIOMEDIN 279: Computational Biology: Structure and Organization of Biomolecules and Cells (CS 279, BIOPHYS 279, BIOE 279, CME 279)
BIOMEDIN 371: Computational Biology in Four Dimensions (CS 371, BIOPHYS 371, CME 371)
BIOMEDIN 374: Algorithms in Biology (CS 374)
BIOMEDIN 472: Data Sciencee and AI for COVID-19 (BIODS 472, CS 472)
BIOPHYS 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOMEDIN 279, BIOE 279, CME 279, CS 279)
BIOPHYS 371: Computational Biology in Four Dimensions (BIOMEDIN 371, CME 371, CS 371)
BIOS 221: Modern Statistics for Modern Biology (STATS 366)
BIOS 234: Personalized Genomic Medicine
CBIO 243: Principles of Cancer Systems Biology
CME 100: Vector Calculus for Engineers (ENGR 154)
CME 102: Ordinary Differential Equations for Engineers (ENGR 155A)
CME 103: Introduction to Matrix Methods (EE 103)
CME 104: Linear Algebra and Partial Differential Equations for Engineers (ENGR 155B)
CME 106: Introduction to Probability and Statistics for Engineers (ENGR 155C)
CME 108: Introdution to Scientific Computing (MATH 114)
CME 151A: Introduction to Data Visualization in D3
CME 200: Linear Algebra with Application to Engineering Computations (ME 300A)
CME 204: Partial Differential Equations in Engineering (ME 300B)
CME 207: Numerical Methods in Engineering and Applied Sciences
CME 211: Software Development for Scientists and Engineers
CME 212: Advanced Software Development for Scientists and Engineers
CME 213: Introduction to Parallel Computing using MPI, openMP, and CUDA
CME 214: Software Design in Modern Fortran for Scientists and Engineers (EARTHSCI 214)
CME 250: Introduction to Machine Learning
CME 250A: Machine Learning on Big Data
CME 251: Geometric and Topological Data Analysis (CS 233)
CME 285: Computational Modeling in the Cardiovascular System (BIOE 285, ME 285)
CME 263: Introduction to Linear Dynamical Systems (EE 263)
CME 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOMEDIN 279, BIOE 279, BIOPHYS 279, CS 279)
CME 292: Advanced MATLAB for Scientific Computing
CME 302: Numerical Linear Algebra
CME 303: Partial Differential Equations of Applied Mathematics (MATH 220)
CME 309: Randomized Algorithms and Probabilistic Analysis (CS 265)
CME 323: Distributed Algorithms and Optimization
CME 330: Applied Mathematics in the Chemical and Biological Sciences (CHEMENG 300)
CME 334: Advanced Methods in Numerical Optimization (MS&E 312)
CME 362: An Introduction to Compressed Sensing (STATS 330)
CME 371: Computational Biology in Four Dimensions (BIOMEDIN 371, BIOPHYS 371, CS 371)
CME 500: Numerical Analysis and Computational and Mathematical Engineering Seminar
CME 510: Linear Algebra and Optimization Seminar
CS 103: Mathematical Foundations of Computing
CS 106A and 106B do NOT count towards this category
CS 107: Computer Organization and Systems
CS 108: Object-Oriented Systems Design
CS 109: Introduction to Probability for Computer Scientists
CS 109L: Statistical Computing with R Laboratory
CS 110: Principles of Computer Systems
CS 111: Operating Systems Principles
CS 124: From Languages to Information (LINGUIST 180, LINGUIST 280)
CS 131: Computer Vision: Foundations and Applications
CS 140: Operating Systems and Systems Programming
CS 142: Web Applications
CS 143: Compilers
CS 144: Introduction to Computer Networking
CS 145: Introduction to Databases
CS 147: Introduction to Human-Computer Interaction Design
CS 148: Introduction to Computer Graphics and Imaging
CS 149: Parallel Computing
CS 154: Introduction to Automata and Complexity Theory
CS 155: Computer and Network Security
CS 157: Logic and Automated Reasoning
CS 161: Design and Analysis of Algorithms
CS 164: Computing with Physical Objects: Algorithms for Shape and Motion
CS 166: Data Structures
CS 167: Readings in Algorithms
CS 193C: Client-Side Internet Technologies
CS 193P: iPhone and iPad Application Programming
CS 205A: Mathematical Methods for Robotics, Vision, and Graphics
CS 205B: Mathematical Methods for Fluids, Solids, and Interfaces
CS 221: Artificial Intelligence: Principles and Techniques
CS 223A: Introduction to Robotics (ME 320)
CS 224D: Deep Learning for Natural Language Processing
CS 224M: Multi-Agent Systems
CS 224N: Natural Language Processing (LINGUIST 284)
CS 224S: Spoken Language Processing (LINGUIST 285)
CS 224U: Natural Language Understanding (LINGUIST 188, LINGUIST 288)
CS 224W: Social and Information Network Analysis
CS 225A: Experimental Robotics
CS 225B: Robot Programming Laboratory
CS 226: Statistical Techniques in Robotics
CS 227B: General Game Playing
CS 228: Probabilistic Graphical Models: Principles and Techniques
CS 229: Machine Learning
CS 229A: Applied Machine Learning
CS 229T: Statistical Learning Theory (STATS 231)
CS 230: Deep Learning
CS 231A: Introduction to Computer Vision
CS 231B: The Cutting Edge of Computer Vision
CS 231N: Convolutional Neural Networks for Visual Recognition
CS 232: Digital Image Processing (EE 368)
CS 236: Deep Generative Models
CS 238: Decision Making under Uncertainty (AA 228)
CS 240: Advanced Topics in Operating Systems
CS 240E: Embedded Wireless Systems
CS 240H: Functional Systems in Haskell
CS 242: Programming Languages
CS 243: Program Analysis and Optimizations
CS 244: Advanced Topics in Networking
CS 244B: Distributed Systems
CS 244C: Readings and Projects in Distributed Systems
CS 244E: Networked Wireless Systems (EE 384E)
CS 245: Database Systems Principles
CS 246: Mining Massive Data Sets
CS 246H: Mining Massive Data Sets Hadoop Lab
CS 248: Interactive Computer Graphics
CS 249A: Object-Oriented Programming from a Modeling and Simulation Perspective
CS 249B: Large-scale Software Development
CS 254: Computational Complexity
CS 255: Introduction to Cryptography
CS 259: Security Analysis of Network Protocols
CS 261: Optimization and Algorithmic Paradigms
CS 262: Computational Genomics (BIOMEDIN 262)
CS 263: Algorithms for Modern Data Models (MS&E 317)
CS 265: Randomized Algorithms and Probabilistic Analysis (CME 309)
CS 266: Parameterized Algorithms and Complexity
CS 267: Graph Algorithms
CS 268: Geometric Algorithms
CS 270: Modeling Biomedical Systems: Ontology, Terminology, Problem Solving (BIOMEDIN 210)
CS 272: Introduction to Biomedical Informatics Research Methodology (BIOE 212, BIOMEDIN 212, GENE 212)
CS 273A: A Computational Tour of the Human Genome (BIOMEDIN 273A, DBIO 273A)
CS 273B: Deep Learning in Genomics and Biomedicine (BIODS 237, BIOMEDIN 273B, GENE 236)
CS 274: Representations and Algorithms for Computational Molecular Biology (BIOE 214, BIOMEDIN 214, GENE 214)
CS 275: Translational Bioinformatics (BIOMEDIN 217)
CS 276: Information Retrieval and Web Search (LINGUIST 286)
CS 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOMEDIN 279, BIOPHYS 279, BIOE 279, CME 279)
CS 295: Software Engineering
CS 309A: Cloud Computing
CS 315A: Parallel Computer Architecture and Programming
CS 315B: Parallel Computing Research Project
CS 316: Advanced Multi-Core Systems (EE 382E)
CS 319: Topics in Digital Systems
CS 328: Topics in Computer Vision
CS 329: Topics in Artificial Intelligence
CS 331A: Advanced Reading in Computer Vision
CS 331B: 3D Representation and Recognition
CS 334A: Convex Optimization I (CME 364A, EE 364A)
CS 340: Topics in Computer Systems
CS 341: Project in Mining Massive Data Sets
CS 343: Advanced Topics in Compilers
CS 344: Topics in Computer Networks
CS 344E: Advanced Wireless Networks
CS 345: Advanced Topics in Database Systems
CS 347: Parallel and Distributed Data Management
CS 348A: Computer Graphics: Geometric Modeling
CS 348B: Computer Graphics: Image Synthesis Techniques
CS 349: Topics in Programming Systems
CS 349C: Topics in Programming Systems: Readings in Distributed Systems
CS 354: Topics in Circuit Complexity
CS 355: Advanced Topics in Cryptography
CS 357: Advanced Topics in Formal Methods
CS 358: Topics in Programming Language Theory
CS 359: Topics in the Theory of Computation
CS 361A: Advanced Algorithms
CS 361B: Advanced Algorithms
CS 362: Algorithmic Frontiers: Effective Algorithms for Large Data
CS 364A: Algorithmic Game Theory
CS 364B: Topics in Algorithmic Game Theory
CS 366: Graph Partitioning and Expanders
CS 367: Algebraic Graph Algorithms
CS 369: Topics in Analysis of Algorithms
CS 369N: Beyond Worst-Case Analysis
CS 371: Computational Biology in Four Dimensions (BIOMEDIN 371, BIOPHYS 371, CME 371)
CS 373: Statistical and Machine Learning Methods for Genomics (BIO 268, BIOMEDIN 245, GENE 245, STATS 345)
CS 374: Algorithms in Biology (BIOMEDIN 374)
CS 375: Large-Scale Neural Network Modeling for Neuroscience (PSYCH 249)
CS 379C: Computational Models of the Neocortex
CS 427: Hero's Journey: AI and Game Theory in 3D Real-time Storytelling
CS 431: High-Level Vision: Object Representation (PSYCH 250)
CS 442: High Productivity and Performance with Domain-specific Languages in Scala
CS 447: Software Design Experiences
CS 448: Topics in Computer Graphics
CS 448B: Data Visualization
CS 468: Topics in Geometric Algorithms: Differential Geometry for Computer Science
CS 520: Knowledge Graphs
CS 522: Seminar in Artificial Intelligence in Healthcare
CS 545: Database and Information Management Seminar
CS 547: Human-Computer Interaction Seminar
CS 528: Machine Learning Systems Seminar
DBIO 273A: A Computational Tour of the Human Genome (BIOMEDIN 273A, CS 273A)
EE 101A: Circuits I
EE 101B: Circuits II
EE 102A: Signal Processing and Linear Systems I
EE 102B: Signal Processing and Linear Systems II
EE 103: Introduction to Matrix Methods (CME 103)
EE 108A: Digital Systems I
EE 108B: Digital Systems II
EE 168: Introduction to Digital Image Processing
EE 169: Introduction to Bioimaging
EE 179: Analog and Digital Communication Systems
EE 248: Fundamentals of Noise Processes
EE 256: Numerical Electromagnetics
EE 257: Applied Optimization Laboratory (Geophys 258) (GEOPHYS 258)
EE 261: The Fourier Transform and Its Applications
EE 262: Two-Dimensional Imaging
EE 263: Introduction to Linear Dynamical Systems (CME 263)
EE 264: Digital Signal Processing
EE 277: Reinforcement Learning: Behaviors and Applications (MS&E 237)
EE 278A: Probabilistic Systems Analysis (EE 178)
EE 278B: Introduction to Statistical Signal Processing
EE 279: Introduction to Digital Communication
EE 282: Computer Systems Architecture
EE 284: Introduction to Computer Networks
EE 292M: Parallel Processors Beyond Multi-Core Processing
EE 361: Principles of Cooperation in Wireless Networks
EE 364A: Convex Optimization I (CME 364A, CS 334A)
EE 364B: Convex Optimization II (CME 364B)
EE 365: Stochastic Control
EE 368: Digital Image Processing (CS 232)
EE 369A: Medical Imaging Systems I
EE 369B: Medical Imaging Systems II
EE 369C: Medical Image Reconstruction
EE 373A: Adaptive Signal Processing
EE 373B: Adaptive Neural Networks
EE 376A: Information Theory (STATS 376A)
EE 376B: Network Information Theory (STATS 376B)
EE 376C: Universal Schemes in Information Theory
EE 378A: Statistical Signal Processing
EE 378B: Inference, Estimation, and Information Processing
EE 379: Digital Communication
EE 382C: Interconnection Networks
EE 382E: Advanced Multi-Core Systems (CS 316)
EE 384A: Internet Routing Protocols and Standards
EE 384C: Wireless Local and Wide Area Networks
EE 384E: Networked Wireless Systems (CS 244E)
EE 384M: Network Science
EE 384S: Performance Engineering of Computer Systems & Networks
EE 386: Robust System Design
EE 387: Algebraic Error Control Codes
EE 388: Modern Coding Theory
EE 398A: Image and Video Compression
EE 464: Semidefinite Optimization and Algebraic Techniques
EPI 206: Meta-research: Appraising Research Findings, Bias, and Meta-analysis
EPI 225: Introduction to Epidemiologic and Clinical Research Methods
EPI 226: Intermediate Epidemiologic and Clinical Research Methods
EPI 239: Applications of Causal Inference Methods (EDUC 260 A, STATS 209B)
EPI 251: Design and Conduct of Clinical Trials
EPI 258: Introduction to Probability and Statistics for Clinical Research
EPI 259 : Introduction to Probability and Statistics for Epidemiology (HUMBIO 89X)
EPI 262: Intermediate Biostatistics: Regression, Prediction, Survival Analysis (STATS 262)
ENGR 150: Data Challenge Lab
ENGR 154: Vector Calculus for Engineers (CME 100)
ENGR 155A: Ordinary Differential Equations for Engineers (CME 102)
ENGR 155B: Linear Algebra and Partial Differential Equations for Engineers (CME 104)
ENGR 155C: Introduction to Probability and Statistics for Engineers (CME 106)
ENGR 205: Introduction to Control Design Techniques
ENGR 206: Control System Design
ENGR 207A: Linear Control Systems I
ENGR 207B: Linear Control Systems II
ENGR 209A: Analysis and Control of Nonlinear Systems
GENE 236: Deep Learning in Genomics and Biomedicine (BIODS 237, BIOMEDIN 273B, CS 273B)
GENE 244: Introduction to Statistical Genetics (STATS 345)
HRP 252: Outcomes Analysis (BIOMEDIN 251, MED 252)
HRP 255: Decoding Academia: Power, Hierarchies, and Transforming Institutions
IMMUNOL 206A: Systems and Computational Immunology
IMMUNOL 206B: Directed Projects in Systems and Computational Immunology
IMMUNOL 207: Essential Methods in Computational and Systems Immunology
IMMUNOL 208: Advanced Computational and Systems Immunology
MATH 104: Applied Matrix Theory
MATH 106: Functions of a Complex Variable
MATH 107: Graph Theory
MATH 108: Introduction to Combinatorics and Its Applications
MATH 109: Applied Group Theory
MATH 110: Applied Number Theory and Field Theory
MATH 111: Computational Commutative Algebra
MATH 113: Linear Algebra and Matrix Theory
MATH 114: Introdution to Scientific Computing (CME 108)
MATH 115: Functions of a Real Variable
MATH 116: Complex Analysis
MATH 118: Mathematics of Computation
MATH 120: Groups and Rings
MATH 121: Galois Theory
MATH 122: Modules and Group Representations
MATH 131P: Partial Differential Equations I
MATH 132: Partial Differential Equations II
MATH 136: Stochastic Processes (STATS 219)
MATH 137: Mathematical Methods of Classical Mechanics
MATH 143: Differential Geometry
MATH 144: Riemannian Geometry
MATH 145: Algebraic Geometry
MATH 146: Analysis on Manifolds
MATH 147: Differential Topology
MATH 148: Algebraic Topology
MATH 149: Applied Algebraic Topology
MATH 151: Introduction to Probability Theory
MATH 152: Elementary Theory of Numbers
MATH 154: Algebraic Number Theory
MATH 155: Analytic Number Theory
MATH 159: Discrete Probabilistic Methods
MATH 161: Set Theory
MATH 171: Fundamental Concepts of Analysis
MATH 172: Lebesgue Integration and Fourier Analysis
MATH 173: Theory of Partial Differential Equations
MATH 174: Calculus of Variations
MATH 175: Elementary Functional Analysis
MATH 193: Polya Problem Solving Seminar
MATH 205A: Real Analysis
MATH 205B: Real Analysis
MATH 210A: Modern Algebra I
MATH 210B: Modern Algebra II
MATH 210C: Lie Theory
MATH 215A: Complex Analysis, Geometry, and Topology
MATH 215B: Complex Analysis, Geometry, and Topology
MATH 215C: Complex Analysis, Geometry, and Topology
MATH 216A: Introduction to Algebraic Geometry
MATH 216B: Introduction to Algebraic Geometry
MATH 216C: Introduction to Algebraic Geometry
MATH 217A: Differential Geometry
MATH 220: Partial Differential Equations of Applied Mathematics (CME 303)
MATH 221A: Mathematical Methods of Imaging (CME 321A)
MATH 221B: Mathematical Methods of Imaging (CME 321B)
MATH 222: Computational Methods for Fronts, Interfaces, and Waves
MATH 224: Topics in Mathematical Biology
MATH 226: Numerical Solution of Partial Differential Equations (CME 306)
MATH 227: Partial Differential Equations and Diffusion Processes
MATH 228: Stochastic Methods in Engineering (CME 308)
MATH 230A: Theory of Probability (STATS 310A)
MATH 230B: Theory of Probability (STATS 310B)
MATH 230C: Theory of Probability (STATS 310C)
MATH 231A: An Introduction to Random Matrix Theory (STATS 351A)
MATH 231C: Free Probability
MATH 232: Topics in Probability: Percolation Theory
MATH 233: Probabilistic Methods in Analysis
MATH 234: Large Deviations Theory (STATS 374)
MATH 236: Introduction to Stochastic Differential Equations
MATH 239: Computation and Simulation in Finance
MATH 243: Functions of Several Complex Variables
MATH 244: Riemann Surfaces
MATH 245A: Topics in Algebraic Geometry: Moduli Theory
MATH 245B: Topics in Algebraic Geometry: Intersection Theory
MATH 245C: Topics in Algebraic Geometry: Alterations
MATH 247: Topics in Group Theory
MATH 248: Ergodic Theory and Szemeredi's Theorem
MATH 248A: Algebraic Number Theory
MATH 249A: Topics in number theory
MATH 249B: Topics in Number Theory
MATH 249C: Topics in Number Theory
MATH 252: Algebraic Groups
MATH 254: Geometric Methods in the Theory of Ordinary Differential Equations
MATH 256A: Partial Differential Equations
MATH 256B: Partial Differential Equations
MATH 257A: Symplectic Geometry and Topology
MATH 257B: Symplectic Geometry and Topology
MATH 257C: Symplectic Geometry and Topology
MATH 258: Topics in Geometric Analysis
MATH 259: mirror symmetry
MATH 261A: Functional Analysis
MATH 263A: Lie Groups and Lie Algebras
MATH 264: Infinite Dimensional Lie Algebra
MATH 266: Computational Signal Processing and Wavelets
MATH 269: Topics in symplectic geometry
MATH 270: Geometry and Topology of Complex Manifolds
MATH 271: The H-Principle
MATH 272: Topics in Partial Differential Equations
MATH 280: Evolution Equations in Differential Geometry
MATH 282A: Low Dimensional Topology
MATH 282B: Homotopy Theory
MATH 282C: Fiber Bundles and Cobordism
MATH 283: Topics in Algebraic and Geometric Topology
MATH 283A: Topics in Topology
MATH 284: Topics in Geometric Topology
MATH 284A: Geometry and Topology in Dimension 3
MATH 284B: Geometry and Topology in Dimension 3
MATH 286: Topics in Differential Geometry
MATH 287: Introduction to optimal transportation
MATH 295: Computation and Algorithms in Mathematics
MATH 301: Advanced Topics in Convex Optimization
MATH 310: Algorithms
MATH 384: Seminar in Geometry
MATH 385: Seminar in Topology
MATH 388: Seminar in Probability and Stochastic Processes
MATH 389: Seminar in Mathematical Biology
MATH 394: Classics in Analysis
MATH 395: Classics in Geometry and Topology
MGTECON 634: Machine Learning and Causal Inference
ME 285: Computational Modeling in the Cardiovascular System (BIOE 285, CME 285)
ME 261: Dynamic Systems, Vibrations and Control (ME 161)
ME 300B: Partial Differential Equations in Engineering (CME 204)
MED 206: Meta-research: Appraising Research Findings, Bias, and Meta-analysis (HRP 206, STATS 211)
MED 263: Advanced Decision Science Methods and Modeling in Health (HRP 263)
MED 252: Outcomes Analysis (BIOMEDIN 251, HRP 252)
MI 245: Computational Modeling of Microbial Communities (BIOE 115)
MS&E 120: Probabilistic Analysis
MS&E 211: Linear and Nonlinear Optimization
MS&E 220: Probabilistic Analysis
MS&E 223: Simulation
MS&E 226: "Small" Data
MS&E 228: Applied Causal Inference with Machine Learning and AI
MS&E 252: Decision Analysis I: Foundations of Decision Analysis
MS&E 263: Healthcare Operations Management
MS&E 310: Linear Programming
MS&E 312: Advanced Methods in Numerical Optimization (CME 334)
MS&E 328: Foundations of Causal Machine Learning
MS&E 335: Queueing and Scheduling in Processing Networks
MS&E 352: Decision Analysis II: Professional Decision Analysis
MS&E 355: Influence Diagrams and Probabilistics Networks
MS&E 454: Decision Analysis Seminar
MS&E 463: Healthcare Systems Design
NBIO 228: Mathematical Tools for Neuroscience
NENS 230: Analysis Techniques for the Biosciences Using MATLAB
OIT 673: Data-driven Decision Making and Applications in Healthcare
PSYCH 248: Advanced fMRI modeling and analysis
PSYCH 248A: fMRI Analysis Bootcamp
PSYCH 253: Advanced Statistical Modeling
STATS 110: Statistical Methods in Engineering and the Physical Sciences
STATS 116: Theory of Probability
STATS 166: Computational Algorithms for Statistical Genetics (GENE 245, STATS 345)
STATS 191: Introduction to Applied Statistics
STATS 200: Introduction to Statistical Inference
STATS 201: Design and Analysis of Experiments
STATS 202: Data Mining and Analysis
STATS 203: Introduction to Regression Models and Analysis of Variance
STATS 205: Introduction to Nonparametric Statistics
STATS 206: Applied Multivariate Analysis
STATS 207: Introduction to Time Series Analysis
STATS 208: Introduction to the Bootstrap
STATS 209: STATS 209: Introduction to Causal Inference
STATS 209B: Applications of Causal Inference Methods
STATS 211: Meta-research: Appraising Research Findings, Bias, and Meta-analysis (HRP 206, MED 206)
STATS 212: Applied Statistics with SAS
STATS 213: Introduction to Graphical Models
STATS 215: Statistical Models in Biology
STATS 216: Introduction to Statistical Learning
STATS 216V: Introduction to Statistical Learning
STATS 217: Introduction to Stochastic Processes
STATS 218: Introduction to Stochastic Processes
STATS 219: Stochastic Processes (MATH 136)
STATS 222: Statistical Methods for Longitudinal Data (EDUC 351A)
STATS 231: Statistical Learning Theory (CS 229T)
STATS 245: Data, Models, and Decision Analytics
STATS 253: Spatial Statistics (STATS 352)
STATS 260A: Workshop in Biostatistics (BIODS 260A)
STATS 260B: Workshop in Biostatistics (BIODS 260B)
STATS 260C: Workshop in Biostatistics (BIODS 260C)
STATS 261: Intermediate Biostatistics: Analysis of Discrete Data (BIOMEDIN 233, HRP 261)
STATS 262: Intermediate Biostatistics: Regression, Prediction, Survival Analysis (HRP 262)
STATS 270: A Course in Bayesian Statistics (STATS 370)
STATS 285: Massive Computational Experiments, Painlessly
STATS 290: Paradigms for Computing with Data
STATS 300: Advanced Topics in Statistics
STATS 300A: Theory of Statistics
STATS 300B: Theory of Statistics
STATS 300C: Theory of Statistics
STATS 305A: Applied Statistics I
STATS 305B: Applied Statistics II
STATS 305C: Applied Statistics III
STATS 306A: Methods for Applied Statistics
STATS 306B: Methods for Applied Statistics: Unsupervised Learning
STATS 310A: Theory of Probability (MATH 230A)
STATS 310B: Theory of Probability (MATH 230B)
STATS 310C: Theory of Probability (MATH 230C)
STATS 314: Advanced Statistical Methods
STATS 315A: Modern Applied Statistics: Learning
STATS 315B: Modern Applied Statistics: Data Mining
STATS 316: Stochastic Processes on Graphs
STATS 317: Stochastic Processes
STATS 318: Modern Markov Chains
STATS 319: Literature of Statistics
STATS 320: Heterogeneous Data with Kernels
STATS 321: Modern Applied Statistics: Transposable Data
STATS 322: Function Estimation in White Noise
STATS 324: Multivariate Analysis
STATS 325: Multivariate Analysis and Random Matrices in Statistics
STATS 329: Large-Scale Simultaneous Inference
STATS 330: An Introduction to Compressed Sensing (CME 362)
STATS 338: Topics in Biostatistics
STATS 341: Applied Multivariate Statistics
STATS 345: Introduction to Statistical Genetics (GENE 244)
STATS 345: Computational Algorithms for Statistical Genetics (GENE 245, STATS 166)
STATS 351A: An Introduction to Random Matrix Theory (MATH 231A)
STATS 352: Spatial Statistics (STATS 253)
STATS 355: Observational Studies (HRP 255)
STATS 362: Monte Carlo
STATS 366: Modern Statistics for Modern Biology (BIOS 221)
STATS 367: Statistical Models in Genetics
STATS 370: A Course in Bayesian Statistics (STATS 270)
STATS 374: Large Deviations Theory (MATH 234)
STATS 375: Inference in Graphical Models
STATS 376A: Information Theory (EE 376A)
STATS 396: Research Workshop in Computational Biology