Ali Cafer Gurbuz, PhD Home Research Publications Teaching IMPRESS Lab Group


Classes Taught at MSU

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ECE 4990/6990 Mathematical Foundations of Machine Learning

Course Offered: Spring 2020 (Designed and offered first time at MSU)

Brief Course Detail: It is very important for engineering graduates to learn, apply and develop the necessary tools and fundamental background in data science, machine learning and artificial intelligence areas. Currently the general machine learning tools are given to the students as black boxes where the students learn to apply the tool in a given application using predefined settings or functions in programming environments. Although this is important, engineering students should have also solid mathematical knowledge and foundations of learning techniques to understand the basics of machine learning tools, extend and develop new techniques in this area rather than only being able to use the tools provided in different programming environments.
The purpose of this course is to provide senior, masters or first year PhD students in engineering and computing with a solid mathematical background of modern data science in linear algebra. signal processing and applied probability. Mathematical background of both supervised and unsupervised machine learning will be introduced.

Syllabus

ECE 8433 Statistical Signal Processing

Course Offered: Spring 2019

Brief Course Detail: The primary goal of this course is to introduce graduate students to the mathematical ideas that form the basis for modern statistically-based analysis of signals and systems. These methods are used in a wide range of engineering applications and form the fundementals of many current machine learning and deep learning approaches. Students will understand the fundementals tasks such as detection, classification and estimation with the underlying statistical/mathematical properties.

Syllabus

ECE 3443 Signals and Systems

Course Offered: Spring 2019, Fall 2020

Brief Course Detail: The objectives of this course are to introduce students to the basic concepts of signals, system modeling, and system classification; to develop students’ understanding of time-domain and frequency domain approaches to the analysis of continuous and discrete systems; to provide students with necessary tools and techniques to analyze systems and data; and to develop students’ ability to apply modern simulation software to system analysis.

Syllabus

ECE 3313 Electromagnetics I

Course Offered: Fall 2018

Brief Course Detail: The objective of this course is to teach the fundemental laws and concepts governing the electromagnetic principles in the world. Students will understand important conceptd including Static and dynamic electromagnetic (EM) fields, energy, and power, EM fields and waves within and at the boundaries of media, EM radiation and propagation in space and within transmission lines.

Syllabus



Classes Taught Prior to MSU


Undergraduate classes at TOBB University:

  • ELE 201 Circuit Analysis I / Lab
  • ELE 202 Circuit Analysis II
  • ELE 371 Signals and Systems
  • ELE 474 Digital Signal Processing
  • ELE 480 Introduction to Estimation
  • ELE 495 Undergraduate Project


Graduate classes at TOBB University:

  • ELE 465/565 Fundamentals of Radar Signal Processing
  • ELE 571 Detection and Estimation (established and offered first time at the university)
  • ELE 670 Radar Signal Processing (established and offered first time at the university)
  • ELE 675 Array Signal Processing (established and offered first time at the university)