Wearable Devices and Computer Vision

Harvard Extension School

DGMD E-14

Section 1

CRN 16693

View Course Details
This course explores the field of wearable devices and computer vision, two technologies experiencing a modern-day renaissance. Wearable technologies is an exciting, innovative field that has seen a flurry of recent advancements, such as the Apple Vision Pro, which is Apple's first augmented/mixed-reality device; Ray-Ban Stories, which are designer smart glasses to capture and share moments on social media; and various artificial intelligence (AI)-enable wearables, which aim to integrate AI-powered personal assistants with clothing and jewelry. Underlying these advances in wearable devices is computer vision, which is an exciting field of AI and machine learning, enabling computers to derive information from images, videos, and other inputs. In this course, we explore wearable devices and utilize computer vision to tackle emerging problems (for example, assistive devices, educational applications, and health monitoring). Students learn about sensors, signal processing, data analytics, AI, machine learning, computational image processing, neural networks, localization and mapping, and robust algorithms for modeling. By the end of this course, students are ready to join the community of pioneers and innovators making the future of wearable and computer vision technology. Students may not take both DGMD E-13 and DGMD E-14 for degree or certificate credit.

Instructor Info

Nabib Ahmed, AM

Artificial Intelligence Researcher, Meta


Meeting Info

T 5:30pm - 7:30pm (9/2 - 12/20)

Participation Option: Online Asynchronous or Online Synchronous

In online asynchronous courses, you are not required to attend class at a particular time. Instead you can complete the course work on your own schedule each week.

Deadlines

Last day to register: August 28, 2025

Prerequisites

CSCI E-7 or CSCI E-50 or equivalent. Experience with programming, technical and code documentation, and data (any programming language will do; some examples are Python, R, Java, or C/C++). Familiarity with algebra and geometry. No background needed in machine learning, computer vision, or wearable devices.

Notes

This course meets via web conference. Students may attend at the scheduled meeting time or watch recorded sessions asynchronously. Recorded sessions are typically available within a few hours of the end of class and no later than the following business day. See minimum technology requirements.

All Sections of this Course

CRN Section # Participation Option(s) Instructor Section Status Meets Term Dates
34484 1 Online Asynchronous, Online Synchronous Nabib Ahmed Open TTh 6:30pm - 9:30pm
Jun 23 to Aug 8
16693 1 Online Asynchronous, Online Synchronous Nabib Ahmed Open T 5:30pm - 7:30pm
Sep 2 to Dec 20