Coursera

Introduction to Image Processing (Coursera)

Offered by MathWorks,

In this introduction to image processing, you'll take your first steps in accessing and adjusting digital images for analysis and processing. You will load, save, and adjust image size and orientation while also understanding how digital images are recognized. You will then perform basic segmentation and quantitative analysis. Lastly, you will enhance the contrast of images to make objects of interest easier to identify.

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

By the end of the course, you’ll apply your segmentation skills to identify regions of interest, such as the amount of surface water from satellite images. This introduction to image processing will give you the foundation you need to conduct more advanced work on this topic.
You will use MATLAB throughout this course. MATLAB is the go-to choice for millions of people working in engineering and science and provides the capabilities you need to accomplish your image processing tasks. You will be provided with free access to MATLAB for the duration of the course to complete your work.
To be successful in this course you should have a background in basic math and some exposure to MATLAB. If you want to familiarize yourself with MATLAB check out the free, two-hour MATLAB Onramp. Experience with image processing is not required.
Course 1 of 3 in the Image Processing for Engineering and Science Specialization.

Syllabus

WEEK 1: Introduction to Digital Images
WEEK 2: Working with Image Data
WEEK 3: Thresholding Images
WEEK 4: Adjusting Image Contrast

Go to Class

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

Related Courses

Coursera

Michigan State University

Principles of Photo Composition and Digital Image Post-Production (Coursera)

Film & Audio

Welcome to Course THREE! In the first two Modules you will gain a more professional-level understanding of the Design Elements that artists have used throughout history to create successful compositions. Arranging the Elements in ways that lead viewers through their compositions is an essential craft for photographers no matter whether their subject matter is pure documentary or vividly exotic personal expression.

Nov 9th 2026

4 Weeks

Photography Composition Digital Image

Coursera

Columbia University

Camera and Imaging (Coursera)

CS: Software Engineering Computer Science

This course covers the fundamentals of imaging – the creation of an image that is ready for consumption or processing by a human or a machine. Imaging has a long history, spanning several centuries. But the advances made in the last three decades have revolutionized the camera and dramatically improved the robustness and accuracy of computer vision systems. We describe the fundamentals of imaging, as well as recent innovations in imaging that have had a profound impact on computer vision.

Nov 2nd 2026

5-12 Weeks

Image Computer Vision Image Processing

Coursera

DeepLearning.AI

Advanced Computer Vision with TensorFlow (Coursera)

Data Science

In this course, you will: a) Explore image classification, image segmentation, object localization, and object detection. Apply transfer learning to object localization and detection; b) Apply object detection models such as regional-CNN and ResNet-50, customize existing models, and build your own models to detect, localize, and label your own rubber duck images; c) Implement image segmentation using variations of the fully convolutional network (FCN) including U-Net and d) Mask-RCNN to identify and detect numbers, pets, zombies, and more; d) Identify which parts of an image are being used by your model to make its predictions using class activation maps and saliency maps and apply these ML interpretation methods to inspect and improve the design of a famous network, AlexNet.

Nov 9th 2026

4 Weeks

ML Computer Vision Visualization

Coursera

MathWorks

Object Tracking and Motion Detection with Computer Vision (Coursera)

Engineering

In the third and final course of the Computer Vision for Engineering and Science specialization, you will learn to track objects and detect motion in videos. Tracking objects and detecting motion are difficult tasks but are required for applications as varied as microbiology and autonomous systems. To track objects, you first need to detect them. You’ll use pre-trained deep neural networks to perform object detection. You’ll also use optical flow to detect motion and use the results to detect moving objects.

Nov 2nd 2026

4 Weeks

MATLAB Computer Vision Object Detection

Coursera

Instituto Tecnológico de Aeronáutica

Controle de Sistemas no Plano-s (Coursera)

Engineering

Após esse curso você será capaz de esboçar o Lugar Geométrico das Raízes (LGR - Root Locus) do denominador da Função de Transferência em Malha Fechada a partir dos polos e zeros da Função de Transferência em Malha aberta. Você também será capaz de projetar controladores de avanço de fase para atender simultaneamente requisitos de desempenho de amortecimento e de velocidade da resposta.

Nov 23rd 2026

5-12 Weeks

MATLAB Engineering Simulation

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.

Nov 2nd 2026

4 Weeks

MATLAB Computer Vision Computer Programming

Coursera

Stanford University

Machine Learning (Coursera)

Statistics & Data Analysis Data Science

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Nov 2nd 2026

5-12 Weeks

Artificial Intelligence MATLAB Algorithms

Coursera

MathWorks

Data Science Companion (Coursera)

Statistics & Data Analysis Data Science

The Data Science Companion provides an introduction to data science. You will gain a quick background in data science and core machine learning concepts, such as regression and classification. You’ll be introduced to the practical knowledge of data processing and visualization using low-code solutions, as well as an overview of the ways to integrate multiple tools effectively to solve data science problems.

Nov 6th 2026

4 Weeks

MATLAB Machine Learning Regression

Coursera

The Hong Kong University of Science and Technology - HKUST

Numerical Methods for Engineers (Coursera)

Sci: Mathematics

Numerical Methods for Engineers covers the most important numerical methods that an engineer should know. We derive basic algorithms in root finding, matrix algebra, integration and interpolation, ordinary and partial differential equations. We learn how to use MATLAB to solve numerical problems. Access to MATLAB online and the MATLAB grader is given to all students who enroll. We assume students are already familiar with the basics of matrix algebra, differential equations, and vector calculus. Students should have already studied a programming language, and be willing to learn MATLAB.

Nov 2nd 2026

5-12 Weeks

Algebra MATLAB Matrix

Coursera

Duke University

Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera)

Engineering Sci: Mathematics

In this course, you will learn the science behind how digital images and video are made, altered, stored, and used. We will look at the vast world of digital imaging, from how computers and digital cameras form images to how digital special effects are used in Hollywood movies to how the Mars Rover was able to send photographs across millions of miles of space.

Nov 2nd 2026

5-12 Weeks

Math Image Video

Coursera

MathWorks

Automating Image Processing (Coursera)

CS: Software Engineering

In this course, you will build on the skills acquired in Image Segmentation, Filtering, and Region Analysis to explore large sets of images and video files. It’s impractical to manually inspect results in large data sets. Automating image processing allows you to do your work more efficiently.

Nov 9th 2026

4 Weeks

MATLAB Video Processing Image Processing

Coursera

Vanderbilt University

Mastering Programming with MATLAB (Coursera)

CS: Software Engineering CS: Programming

The course builds on the foundation laid by the first course of the Specialization called “Introduction to Programming with MATLAB.” It covers more advanced programming concepts such as recursion, vectorization, function handles, algorithm efficiency and others. At the same time, it presents many features that make MATLAB a powerful programming environment for engineering and scientific computing, such as its support for object oriented programming, the new user interface design environment and Live Scripts.

Nov 9th 2026

5-12 Weeks

Programming MATLAB Object-Oriented Programming