Free Course

Intel® Edge AI Fundamentals with OpenVINO™

Develop cutting-edge Edge AI applications

About this Course

Stay at the cutting-edge of AI technology by gaining practical skills for deploying edge AI. Learn how to use the Intel® Distribution of the OpenVINO™ toolkit to deploy computer vision capabilities inside a range of edge applications. Leverage the potential of edge computing and use the Intel® Distribution of the OpenVINO™ toolkit to fast-track development of high-performance computer vision and deep learning inference applications.

Course Cost
Free
Timeline
Approx. 1 month
Skill Level
intermediate
Included in Product

Rich Learning ContentRich Learning Content

Interactive QuizzesInteractive Quizzes

Taught by Industry ProsTaught by Industry Pros

Self-Paced LearningSelf-Paced Learning

Course Leads

Michael Virgo

Michael Virgo

Senior Curriculum Manager

Prerequisites and Requirements

Basic Python experience. Basic familiarity with computer vision and AI model creation.

See the Technology Requirements for using Udacity.

Why Take This Course

Computer vision and AI at the edge are becoming instrumental in powering everything from factory assembly lines and retail inventory management to hospital urgent care medical imaging equipment like X-ray and CAT scans. This program will teach fluency in some of the most cutting-edge technologies. The course will introduce students to the Intel® Distribution of OpenVINO™ Toolkit, which allows developers to deploy pre-trained deep learning models through a high-level C++ or Python inference engine API integrated with application logic. Based on convolutional neural networks (CNN), the toolkit extends workloads across Intel® hardware (including accelerators) and maximizes performance.

What is Edge AI? In Edge AI, the AI algorithms are processed locally on a hardware device, without requiring any connection. It uses data that is generated from the device and processes it to give real-time insights in less than few milliseconds. AI Edge processing today is focused on moving the inference part of the AI workflow to the device, keeping data constrained to the device.

What do I get?
  • Instructor videos
  • Learn by doing exercises
  • Taught by industry professionals