Edge AI Certification Program

This is an introductory level course for machine learning. The main part of this course will be supervised learning. A small part of unsupervised learning and conceptual part of the neural network will be explored in this class as well. Topics covered include:

• Overview of Machine Learning
• Basic Python Coding
• Linear Regression (Lasso and Ridge)
• Model Selection
• Classification (KNN, SVM, Naïve Bayes)
• K-Means Clustering
• Principle Component Clustering
• Concept of Neural Network

Upon completion of this course the student can use Python machine learning libraries to solve practical problems and visualize data in low dimension space via dimension reduction techniques.

Class start date TBD. Meetings will be synchronous Zoom meetings every Tuesday/Thursday for six weeks.

This course is designed for engineers, scientists, product managers, and decision makers who will drive this revolution of edge AI. It's a high level guide to the entire space of edge AI, providing a workflow and a framework for solving real-world problems using edge AI. Topics covered include:

• Opportunities, limitations, and risks inherent to various Edge AI techniques.
• A framework for analyzing problem and designing solutions using AI and embedded machine learning.
• An end-to-end practical workflow for successfully developing Edge AI applications.

Upon completion of this course the student will have a workflow and framework for solving real world problems using Edge AI.

Class start date TBD. Meetings will be synchronous Zoom meetings every Monday/Wednesday for six weeks.