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Deploying Edge AI

Dates:April 8 - May 15, 2024
Meets:M and W from 6:00 PM to 8:30 PM
Cost: $600.00

Sorry, we are no longer accepting registrations for this course. Please contact our office to find out if it will be rescheduled, or if alternative classes are available.

This course is a high-level guide to the entire space of edge AI. It is designed for engineers, scientists, product managers, and decision makers, providing them a workflow and framework for solving real-world problems using edge AI. It will cover opportunities, limitations and risks inherent to various edge AI technologies and provide a framework for analyzing problems and designing solutions using AI and embedded machine learning. It will also provide an end-to-end workflow for developing AI applications.

This is not a programming course or tutorial providing a lot of line-by-line code explanations or step-by-step guides to using specific software; rather, it is a course on how to apply a general framework to solve problems using whichever tools are best suited for the job.

There will be tangible, interactive examples that can be explored, customized and built upon. Students will also be provided a variety of artifacts to explore--from GIT repositories to free online databases and example training pipelines.

The certificate program consists of four courses. Each course runs for six weeks and meets synchronously on Zoom. The first two courses can be taken simultaneously or in any order to fit your schedule.

Admission to the University is not required, however, students must apply to enter the certificate program to ensure that they have the skills needed to be successful.

Apply at



Learning materials include class slides and notes. No textbook required.
Fee: $600.00


Course is offered via Zoom.

Ali Haidous

Dr. Ali Haidous is a licensed Professional Engineer and has over 12 years of industry experience. He worked and consulted for many Fortune 500 companies and various startups. Ali took his first startup through an acquisition at 21 years old. He earned his B.S. degree in electrical and computer engineering (ECE) from Lipscomb University, M.Eng. and Ph.D. in ECE from North Dakota State University (NDSU). His research primarily focuses on embedded hardware-software AI system integration, video memory optimization for low-power applications, and content aware power efficient smart memory systems leveraging machine learning techniques for big videos and deep learning.
Date Day Time Location
04/08/2024Monday6 PM to 8:30 PM Zoom
04/10/2024Wednesday6 PM to 8:30 PM Zoom
04/15/2024Monday6 PM to 8:30 PM Zoom
04/17/2024Wednesday6 PM to 8:30 PM Zoom
04/22/2024Monday6 PM to 8:30 PM Zoom
04/24/2024Wednesday6 PM to 8:30 PM Zoom
04/29/2024Monday6 PM to 8:30 PM Zoom
05/01/2024Wednesday6 PM to 8:30 PM Zoom
05/06/2024Monday6 PM to 8:30 PM Zoom
05/08/2024Wednesday6 PM to 8:30 PM Zoom
05/13/2024Monday6 PM to 8:30 PM Zoom
05/15/2024Wednesday6 PM to 8:30 PM Zoom