Training Model & Courses Work

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*The list is updated quarterly* Please check schedule for availability

Our training model consists of extensive cross-department courses, lab-rotations, series of workshop and colloquium seminars, regular meetings, NRT student annual conference…. etc.

UCLA NRT Program Courseworks:

Below are the suggested courses for each of the research layers and cores. Students can suggest additional or alternative courses in line with the program goals depending on course offerings in various departments. The list will be updated on a quarterly-basis.

Research Layer 1: Genomics & Genetics

  • CS CM221 Introduction to Bioinformatics
  • CS 224 Computational Genetics
  • CS 225 Computational Methods in Genomics
  • CS 229 Computational Biology
  • Stats M254 Statistical Methods in a Computational Biology, Human Genetics
  • HG 236A Advanced Human Genetics A: Molecular Aspects;
  • HG 236B Advanced Human Genetics B: Statistical Aspects;
  • HG M278 Statistics of DNA Microarray
  • PYSCH 205G Behavior Genetics

Research Layer 2: Brian Imaging and Multi-Modal Prediction

  • Stats 233 Statistical Methods in Biomedical Imaging
  • Stats 203: Large Sample Theory
  • PSCYH 204B Theories of Learning
  • PSYCH 205B Human Neurophysiology
  • PSYCH 205L Cognitive Neurosciences
  • PSYCH M213 Neuroimaging and Brain mapping
  • M219 Principles and Applications of Magnetic Resonance Imaging
  • PSYCH 265 Computational Methods for Neuroimaging
  • M424 Function MRI Journal Club

Research Layer 3: Mobile Sensing and Individual Behaviors

  • M266 (A-E) Applied Differential Equations
  • M 269 (A-E) Numerical Analysis
  • M 238AB Dynamical Systems
  • Geog M205 Spatial Statistics
  • Geog 208 Geographic Data Visualization and Analysis
  • PSCYH 259 Quantitative Methods in Cognitive Psychology
  • Socio 213B Applied Event History Analysis
  • NS 240 Phenotypic Measurement of Complex Traits

Research Layer 4: Social Networks

  • M 276 Topics in Network Science
  • Stats 218 Statistical Analysis of Networks
  • CS M276A Pattern Recognition and Machine Learning
  • ECE 232E Graphs and Network Flows
  • Soc 208A, 208B Social Network Methods
  • Comm 156 Social Networking
  • Stats M231 Pattern Recognition and Machine Learning
  • Stats 170 Introduction to Time-Series Analysis
  • Stats 234 Statistics and Information Theory

Core Area A: Mathematical Modeling and Network Analysis

  • CS 282A/Math 209A: Cybersecurity and Cryptography* (newly added)
  • CS M296A Advanced Modeling Methodology for Dynamic Biomedical Systems
  • M 285J Scientific Computation Course | Epidemic Modeling* (newly added)
  • M 209B Cryptographic Protocols
  • M 270A Techniques of Scientific Computing; Math 270B/C Computational Linear Algebra
  • M 273 Optimization and Calculus of Variations
  • Soc M213A Introduction to Demographic Methods
  • Soc 213C Population Models and Dynamics
  • PoliSci 204A, B, C Game Theory in Politics I, II, III
  • Eco 213B General Equilibrium and Game Theory
  • Econ 412 Fundamentals of Big Data

Core Area B: Scalable Machine Learning and Big Data Analytics

  • CS 247 Advanced Data Mining
  • CS 239 Data Science in Software Engineering
  • CS 249 Big Data Analytics
  • CS 240A Databases and Knowledge Bases
  • CS 240B Data Stream Management Systems and Data Mining Applications
  • EE 239AS: Statistical Machine Learning
  • ECE 239AS Neutral Networks & Deep Learning
  • ECE 231A Information Theory: Channel & Source Coding
  • M 285J Seminar in Machine Learning
  • Stats 236 Introduction to Bayesian Statistics
  • Stats 165 Statistical Methods and Data Mining
  • Econ 413 Data and Analytics and Big Data

Core Area C: Biomedical Applications and Social Outcomes

  • BE M227 Medical Information Infrastructure
  • M217 Biomedical Imaging
  • Anth 229 Current Problems in Biological Anthropology
  • Soc 212C Study Design and Other Issues in Quantitative Data Analysis
  • Soc 234 Sociology of Development
  • PoliSci 200C Casual Inference for Social Science
  • PoliSci 200E Experimental Design for Social Science
  • PoliSci M208E Bayesian Practicum

Technical Communication

  • CS 495 Teaching Assistant Seminar: how to explain things
  • M 495 Teaching College Mathematics
  • ECE 375 Teaching Apprentice Practicum


  • Ethics in Multidisciplinary Data Science and Engineering | Engineering 183 Engineering & Society
  • PSYCH 267 Neuroethics
  • NS 207 Integrity of Scientific Investigation, Education, Research, and Career Implications
  • MIMG C234 Ethics and Accountability in Biomedical Research
  • C250 Research Integrity in Cellular Biology, Molecular Biology, and BioChemistry Research