# Courses

CNEC faculty have developed a number of undergraduate and graduate neural engineering and computation courses. CNEC is also facilitating Master's Degree concentrations in Neural Engineering, and Computation that span all SEAS departments.

**Concentration in Systems Biology & Neuroengineering in the Dept. of Electrical Engineering**

- Satisfy M.S. degree requirements in Electrical Engineering.
- Take both
- Take at least one course from:
- BMEE E4030: Neural control engineering;
- ECBM E4040: Neural Networks and deep learning;
- ECBM E4070 Computing with Brain Circuits of Model Organisms;
- ECBM E4090: Brain computer interfaces (BCI) laboratory;
- CBMF W4761: Computational genomics;
- ELEN E6010: Systems biology: design principles for biological circuits;
- EEBM E6020: Methods in computational neuroscience;
- BMEE E6030: Neural modeling and neuroengineering;

- Take at least one course from:
- ECBM E6040: Neural networks and deep learning research;
- ECBM E607x: Topics in neuroscience and deep learning:
- ELEN E608x: Topics in systems biology;
- EEBM E609x: Topics in Computational Neuroscience and Neuroengineering:
- ELEN E6261: Computational methods of circuit analysis;
- ELEN E6717: Information theory;
- ELEN E6860: Advanced digital signal processing;

**Concentration in Data-Driven Analysis & Computation in the Dept. of Electrical Engineering**

- Satisfy M.S. degree requirements in Electrical Engineering.
- Take at least two courses from:
- ECBM E4040: Neural networks and deep learning;
- EECS E4764: Internet of things – intelligent and connected systems;
- ELEN E4810: Digital Signal Processing;
- ELEN E490x: Topics in Electrical and Computer Engineering:
- ELEN E4903: Topic: Machine learning (or equivalent);

- EEOR E6616: Convex optimization;
- ELEN E688x: Topics in Signal Processing:
- EECS E689x Topics in Information Processing:

- Take at least one course from:
- ECBM E6040: Neural networks and deep learning research;
- EECS E6720: Bayesian models for machine learning;
- EECS E6765: Internet of things - systems and physical data analytics;
- EECS E689x: Topics in Information Processing:
- EECS E6895: Topic: Advanced big data analytics;

- Take a second course from #3, or one course from:
- ECBM E4060: Introduction to Genomic Information Science and Technology;
- ECBM E607x: Topics in Neuroscience and Deep Learning:
- ELEN E669x: Topics in Data-driven Analysis and Computation:
- ELEN E6690: Topic: Statistical Learning in Biological & Information Systems;
- EECS E6699: Topic: Mathematics of Deep Learning;

- ELEN E6886: Sparse representation and high-dimensional geometry;
- ELEN E9601: Seminar in data-driven analysis and computation;