Neural Engineering - Signals, Systems & Machine Learning Graduate Certificate
Gain a fundamental and applied understanding of brain signals and systems and machine learning schemes in the rapidly growing field of neural big-data research. This program includes the study of concepts related to the modeling of electrical circuits in the brain. Gain expertise in understanding the fundamentals of signals, systems and machine learning tools for “reverse engineering the brain” and for the design of neural prostheses and brain machine interfaces.
What is it?
The Graduate Certificate in Neural Engineering – Signals, Systems & Machine Learning is a 12 credit-hour stand-alone certificate. It consists of 6 required credit hours and 6 hours of support courses.
Why pursue it?
Understanding the brain is one of the top challenges for research in our time. This certificate will prepare engineering students to work in neuroscience-related careers, both in industry and academia. The certificate is ideal for current graduate students seeking opportunities in neuroscience and neural engineering research.
Graduate Certificate in Neural Engineering – Signals, Systems & Machine Learning Graduate Certificate
Requirements: 12 completed hours
Required: 6 hours from the set below:
ECE/CS 7540 Neural Models and Machine Learning
ECE 7310 Feedback Control Systems
Or ECE 7830 Introduction to Digital Signal Processing
ECE 7590 Computational Neuroscience (required)
Support courses: 6 hours from the set below:
Any of the three courses above not taken
ECE 8810 Advanced Digital Signal Processing
ECE 8860 Probability and Stochastic Processes for Engineers
ECE/CS 8570 Neural Dynamics and Communication
ECE/CS 8580 Machine Learning in Neuroscience
Current Mizzou students should speak to their advisor about adding the certificate.
Non-Mizzou students can apply for the certificate here.