Signal and Image Processing—Graduate Certificate | College of Engineering

Online Education for Working Professionals

Focus on technologies used in digital and analog signal analyses.

Applications range from medical imaging to autonomous vehicle technology.

Learn data manipulation techniques to improve signal or image fidelity. Understand the theory of probability and stochastic processes. Detect and estimate signals. Use computer programming in digital image processing. Autonomous navigation through sensors relies on process control and computer vision.

This program is no longer accepting applications. Both theDepartment of Electrical and Computer Engineering(ECE) and theCollege of Engineering(COE) offers a variety graduate certificates to meet your needs.

3 courses in 3 semesters.

Department	Electrical and Computer Engineering
Admissions requirement	Electrical or computer engineering, data science, or related degree.
Contact	Paul L. Bergstrom

Length	3 courses in 2-3 semesters
Effort	3 hours per credit per week
Each course	3 credits
Total credits	9
Course type	Online or on-campus
Modality	Watch class recordings on demand
Cost	Based on credits and course type
Already enrolled?	Speak with your advisor

Curriculum

Progress quickly with a compact curriculum. Work with the program advisor to select courses that fit your interests and pre-requisite skills.

Required Courses

Take a 3 credit required course.

EE 5500 - Probability and Stochastic Processes

Theory of probability, random variables, and stochastic processes, with applications in electrical and computer engineering. Probability measure and probability spaces. Random variables, distributions, expectations. Random vectors and sequences. Stochastic processes, including Gaussian and Poisson processes. Stochastic processes in linear systems. Markov chains and related topics.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall
Restrictions: Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering, Electrical & Computer Engineer; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

Electives

Take 6 credits of elective courses.

EE 5300 - Mathematical and Computational Methods in Engineering

Overview of problem-solving tools and techniques in engineering, considered from both the analytical and computational point of view. Systems of linear equations, eigenvalue and eigenvector computations, boundary value and initial value problems, Fourier analysis, large-scale systems, optimization. Mathematical modeling and computar programming.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall, Spring
Restrictions: Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

EE 5521 - Detection & Estimation Theory

Detecting and estimating signals in the presence of noise. Optimal receiver design. Applications in communications, signal processing, and radar.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall, Spring
Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering
Pre-Requisite(s): EE 5500

EE 5522 - Digital Image Processing

Fundamentals of image processing are covered including image representation, geometric transformations, binary image processing, compression, space and frequency domain processing. Computer programming in MATLAB and Python required.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall, Spring
Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering

EE 5532 - Sensing and Processing for Robotics

Sensing modes, signal and image processing for industrial robotic automation processes. Emphasis placed on widely used sensors, including cameras and 3-D sensors for process control and computer vision for autonomous navigation.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Spring
Restrictions: Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
Pre-Requisite(s): EE 5522

Typical Schedule

The minimum completion time is one semester. Here are typical schedules.

Sample Plan 1

Fall
EE 5300 EE 5500 EE 5522

Sample Plan 2

Fall	Spring
EE 5500 EE 5522	EE 5532

Application Process and Admissions Requirements

Applications are reviewed on an individual basis using a holistic approach. Fill out our free graduate application online to apply to any of our programs. Official transcripts and scores are not required for the initial application, although you will need to upload them later.

Graduate School Admissions Process

Applying to the Graduate School is free (no application fees) and fast (no official transcripts, test scores, or letters needed to start). The application process involves three easy steps.

See Admissions Steps

Graduate School Requirements

To be considered for admission to the Graduate School as a degree- or certificate-seeking student, you need to:

have a bachelor's degree or its equivalent from an accredited institution, and
be prepared for advanced study in your chosen field, as demonstrated by your previous degree and your scholastic record.

See additional application requirements, including required materials:

Official Transcripts

Program Specific Requirements

Program Specific

Admitted applicants typically have an undergraduate GPA of 3.0 or better on a 4.0 scale
GMAT/GRE: Not required
Preferred major: Electrical Engineering or closely related technical field - Students with degrees in other fields may be required to take preparatory courses

International Students

TOEFL: Recommended Score of 79 iBT
IELTS: Recommended Overall Band Score of 6.5

Admissions Decisions

Made on a rolling basis.

Certificate Admissions

Prospective Students

Prospective students and non-degree seeking students interested in obtaining a graduate certificate must apply to the certificate program using the online application.
Accelerated certificate options exist for current Michigan Tech undergraduate students in good standing and have achieved at least junior-level standing or recent bachelor’s graduates of Michigan Tech (less than two years).
The number of credits earned prior to admission that can be counted are restricted.

Current Graduate Students

Current Michigan Tech graduate students who are in a degree program do not need to formally apply. Current students must still submit the appropriate degree schedule in order to complete the certificate.

International Student Requirements

International Students must apply and be accepted into a degree-granting program in order to earn a graduate certificate. A non-refundable $10 processing fee per application is required.

See International Applicants

Interested in taking a single, online course? Enroll as a non-degree seeking student.

Upon completion of the Certificate the student should be able to:

Demonstrate proper utilization of signal and image processing techniques.

Students receiving this certificate will have demonstrated the ability to solve open-ended problems in statistical signal and/or image processing from fundamental principles, and be able to apply their solution to real world problems.

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We set out as the Michigan Mining School in 1885 to train mining engineers to better operate copper mines. Today, more than 60 percent of Michigan Tech students are enrolled in our 17 undergraduate and 29 graduate engineering programs across nine departments. Our students and curriculum embrace the spirit of hard work and fortitude our founders once had. Our online graduate courses are the same, robust classes taken by our doctorate and masters candidates, taught directly by highly regarded faculty, with outstanding support from staff. We invite working professionals to join these courses, bring their own experience and challenges as part of the discussion. Leverage the national reputation of Michigan Tech to advance your career in tech leadership.

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