Image Processing for Medical Applications

ISE - ENGR - E535

Level : Graduate

Semester : Spring 2017, 2018

Prerequisite(s) : One programming course, linear algebra and calculus are required. Any machine learning or computer vision course would be helpful, but not necessary.

Course Description :

Learn how to build intelligent algorithms and software for medical imaging that can help medical doctors to treat their patients and researchers to understand how the body works. Students will be familiarized with algorithmic techniques such as tracking, denoising, warping, segmentation, model fitting, optimization and interactive visualization of medical datasets.

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Intelligent Systems I

ISE - ENGR – E221

Level : Undergraduate

Semester : Fall 2017

Prerequisite(s) : Calc I (M211); Calc II (M212); Physics I (P221); Software systems engineering (ENGR – E-111)

Course Description :

This course introduces important concepts about intelligent systems. It provides a basis in mathematical tools and algorithms used in AI and machine learning. It introduces optimization techniques used in Intelligent Systems II. It will describe many current examples and how they are implemented in cloud systems. The course is based on Python for data analytics.

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INTRO TO ISE NEURO-ENGINEERING

ISE-ENGR-E506

Level : graduate

Semester : Fall 2018

Prerequisite(s) : None

Course Description :

The students will learn key concepts of neuroengineering. For example what is plasticity. Furthermore you will learn how to build cool machines for neuroengineering applications but more importantly understand the biology and anatomy of human intelligence

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