Coursera

Foundations of AR (Coursera)

Offered by Meta,
Foundations of AR (Coursera)

In this course, you will learn the basics of augmented reality (AR). You will focus on where AR fits in the XR spectrum, how AR is used, what AR can do today—and in the future—and the various technologies used for building such experiences. You will also learn about computer vision in AR, the software development lifecycle, and careers in AR development.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

By the end of the course, you will be able to:

  • Explain how AR fits into the XR spectrum.
  • Distinguish between AR in social media (Meta Spark), AR on a browser (web AR), and AR in a mobile app (Unity AR).
  • Describe AR’s defining characteristics, affordances, and capabilities.
  • Explain how computer vision relates to AR development.
  • Give an overview of the AR software development lifecycle and production.
  • Describe how AR is used in the marketing, education, gaming and entertainment industries.

To be successful in this course, experience with object oriented programming and basic web development is needed. JavaScript is a plus but not required.

Course 1 of 7 in the Meta AR Developer Professional Certificate.

Syllabus

WEEK 1
Introduction to AR
What is AR? What value does it bring to people? Why are developers drawn to it? In this module, you'll answer these questions, as well as learn about the XR spectrum, tools used to develop AR, computer vision, and hear about career paths for AR developers.

WEEK 2
AR technologies and capabilities
In this module, you will learn about the different types of AR and how businesses and developers choose the right one. You'll also learn about different pieces of hardware and their capabilities. In addition, you'll learn about the devices and development technologies that AR developers use.

WEEK 3
Computer vision
Learn what computer vision is and how it applies to AR development, as well as ways to use it in a project.

WEEK 4
AR software development lifecycle
Learn how the software development cycle factors into how AR developers do their work. You'll also hear about careers in AR development, whether alone or as part of a team. You'll end this course with an exploration of design and accessibility considerations.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

3D Reconstruction - Multiple Viewpoints (Coursera) Coursera
Columbia University

3D Reconstruction - Multiple Viewpoints (Coursera)

Computer Science

This course focuses on the recovery of the 3D structure of a scene from images taken from different viewpoints. We start by first building a comprehensive geometric model of a camera and then develop a method for finding (calibrating) the internal and external parameters of the camera model. Then, we show how two such calibrated cameras, whose relative positions and orientations are known, can be used to recover the 3D structure of the scene. This is what we refer to as simple binocular stereo.

Oct 19th 2026
5-12 Weeks
Computer Vision 3D Reconstruction 3D Structures
Details
Internet of Things: Multimedia Technologies (Coursera) Coursera
University of California, San Diego

Internet of Things: Multimedia Technologies (Coursera)

Engineering CS: Information & Technology

Content is an eminent example of the features that contributed to the success of wireless Internet. Mobile platforms such as the Snapdragon™ processor have special hardware and software capabilities to make acquisition, processing and rendering of multimedia content efficient and cost-effective.

Oct 12th 2026
3 Weeks
Multimedia Computer Vision Electrical Engineering
Details
Visual Perception for Self-Driving Cars (Coursera) Coursera
University of Toronto

Visual Perception for Self-Driving Cars (Coursera)

CS: Software Engineering Computer Science

Welcome to Visual Perception for Self-Driving Cars, the third course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. By the end of this course, you will be able to work with the pinhole camera model, perform intrinsic and extrinsic camera calibration, detect, describe and match image features and design your own convolutional neural networks.

Oct 19th 2026
5-12 Weeks
Neural Networks Computer Science Vehicle Dynamics
Details
Computer Vision Basics (Coursera) Coursera
University at Buffalo,The State University of New York

Computer Vision Basics (Coursera)

Computer Science

By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. They are equipped to identify some key application areas of computer vision and understand the digital imaging process. The course covers crucial elements that enable computer vision: digital signal processing, neuroscience and artificial intelligence.

Oct 19th 2026
4 Weeks
MATLAB Computer Vision Computer Programming
Details
Biomedical Visualisation (Coursera) Coursera
University of Glasgow

Biomedical Visualisation (Coursera)

Health & Society

Visualisation is a rapidly progressive specialty in academia, research and industry, and becoming the future of science. With the advancement of digital technologies and their applications, biomedical visualisation is an evolving and popular field. With new techniques and technologies to image, process and analyse data related to the human body, and its biological processes, it is at the forefront of the digital revolution.

Jun 15th 2026
4 Weeks
Human Anatomy Augmented Reality Visualisation
Details
Introduction to Computer Vision with Watson and OpenCV (Coursera) Coursera
IBM

Introduction to Computer Vision with Watson and OpenCV (Coursera)

Data Science

Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries such as self-driving cars, robotics, augmented reality, face detection in law enforcement agencies. In this beginner-friendly course you will understand about computer vision, and will learn about its various applications across many industries.

Jun 29th 2026
4 Weeks
Python Artificial Intelligence Machine Learning
Details
Landing.AI for Beginners: Build Data Visualization AI Models (Coursera) Coursera
Coursera Project Network

Landing.AI for Beginners: Build Data Visualization AI Models (Coursera)

Data Science

In this 1-hour long project-based course, you'll step into the exciting field of Computer Vision and Generative AI using the LandingLens platform. We'll start by exploring the concept of visual prompting, and initiating a visual prompting project. LandingLens simplifies the model creation, training, and deployment process, making it a user-friendly platform for this endeavor.

Oct 19th 2026
1 Week
Artificial Intelligence Computer Vision Data Visualization
Details
Clasificación de imágenes: ¿cómo reconocer el contenido de una imagen? (Coursera) Coursera
Universitat Autònoma de Barcelona

Clasificación de imágenes: ¿cómo reconocer el contenido de una imagen? (Coursera)

CS: Theory

¿Te interesa la visión por computador? ¿Te gustaría saber cómo se puede reconocer el contenido visual de las imágenes y clasificarlas a partir de su contenido? En este curso aprenderás diferentes métodos de representación y clasificación de imágenes. El temario del curso te permitirá conocer el esquema básico de clasificación de imágenes conocido como Bag of Visual Words.

May 25th 2026
5-12 Weeks
Image Computer Vision Image Classification
Details