Technical Topics
Suggested upper-division technical electives for each BioE concentration at UC Berkeley.
These courses are recommended or taken technical electives by BioEHS Officers.
Cell & Tissue Engineering
| Course | Full Name |
|---|---|
| PubH 142 | Introduction to Probability and Statistics in Biology and Public Health |
| MCB C100A | Biophysical Chemistry: Physical Principles and the Molecules of Life |
| MCB 100B | Biochemistry: Pathways, Mechanisms, and Regulation |
| MCB 102 | Survey of the Principles of Biochemistry and Molecular Biology |
| MCB C130 | Cell Biology: From Discovery to Disease |
| MCB 132 | Biology of Human Cancer |
| MCB 150 | Molecular Immunology |
| MCB 150L | Immunology Laboratory |
| IB 132 | Human Physiology |
| MSE 104 | Materials Characterization |
| MSE 151 | Polymeric Materials |
| NEU 100A | Cellular and Molecular Neurobiology |
| NEU 100B | Circuit, Systems, and Behavioral Neuroscience |
Biomedical Imaging
| Course | Full Name |
|---|---|
| PubH 142 | Introduction to Probability and Statistics in Biology and Public Health |
| EECS 126 | Probability and Random Processes |
| EECS 127 | Optimization Models in Engineering |
| EE 117 | Electromagnetic Fields and Waves |
| EE 118 | Introduction to Optical Engineering |
| EE 120 | Signals and Systems |
| EE 105 | Microelectronic Devices and Circuits |
| EE 140 | Linear Integrated Circuits |
| EE C225E | Principles of Magnetic Resonance Imaging |
| CS 189 | Introduction to Machine Learning |
| CS 180 | Introduction to Computer Vision and Computational Photography |
| CS 182 | Designing, Visualizing and Understanding Deep Neural Networks |
| Physics 110A | Electromagnetism and Optics (Part I) |
| Physics 110B | Electromagnetism and Optics (Part II) |
Biomedical Devices
| Course | Full Name |
|---|---|
| PubH 142 | Introduction to Probability and Statistics in Biology and Public Health |
| EE 105 | Microelectronic Devices and Circuits |
| EE 140 | Linear Integrated Circuits |
| EE 120 | Signals and Systems |
| ME 100 | Electronics for the Internet of Things |
| EECS C106A | Introduction to Robotics |
| EECS 126 | Probability and Random Processes |
| EECS 127 | Optimization Models in Engineering |
Computational & Synthetic Biology
| Course | Full Name |
|---|---|
| PubH 142 | Introduction to Probability and Statistics in Biology and Public Health |
| CS 170 | Efficient Algorithms and Intractable Problems |
| CS 189 | Introduction to Machine Learning |
| CS 182 | Designing, Visualizing and Understanding Deep Neural Networks |
| CS 176 | Algorithms for Computational Biology |
| EECS 126 | Probability and Random Processes |
| EECS 127 | Optimization Models in Engineering |
| MCB 110 | Molecular Biology: Macromolecular Synthesis and Cellular Function |
| MCB 140 | General Genetics |
| Math 110 | Abstract Linear Algebra |
| Data 100 | Principles and Techniques of Data Science |
| Stat 131 | Statistical Methods for Data Science |
| Stat 135 | Concepts of Statistics |
| Stat 151 | Linear Modelling: Theory and Applications |