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  • Computer Vision

Computer Vision Courses

Computer vision courses can help you learn image processing, object detection, facial recognition, and video analysis. You can build skills in feature extraction, image classification, and deep learning techniques. Many courses introduce tools like OpenCV, TensorFlow, and PyTorch, that support implementing algorithms and developing applications that leverage artificial intelligence and AI for visual data interpretation.


Popular Computer Vision Courses and Certifications


  • I

    IBM

    Introduction to Computer Vision and Image Processing

    Skills you'll gain: Computer Vision, Jupyter, Machine Learning Algorithms, IBM Cloud, Deep Learning, Cloud Development, Object Oriented Programming (OOP)

    4.3
    Rating, 4.3 out of 5 stars
    ·
    1.4K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Advanced Computer Vision with TensorFlow

    Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Keras (Neural Network Library), Deep Learning, Visualization (Computer Graphics), Heat Maps, Network Architecture

    4.7
    Rating, 4.7 out of 5 stars
    ·
    529 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Computer Vision

    Skills you'll gain: Image Analysis, Computer Vision, Deep Learning, Generative Model Architectures, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Computer Graphics, Visualization (Computer Graphics), Machine Learning Methods, Artificial Intelligence, Data Ethics, Microsoft Excel, Generative AI, Data Processing, Responsible AI, Unsupervised Learning, Linear Algebra, Data Manipulation, Feature Engineering, Supervised Learning

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    30 reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    C

    Columbia University

    First Principles of Computer Vision

    Skills you'll gain: Computer Vision, Image Quality, Image Analysis, Computer Graphics, 3D Modeling, Photography, Virtual Reality, Visualization (Computer Graphics), Medical Imaging, Artificial Neural Networks, Unsupervised Learning, Graph Theory, Dimensionality Reduction, Mathematical Modeling, Estimation, Machine Learning Algorithms, Color Theory, Algorithms, Automation Engineering, Electronic Components

    4.7
    Rating, 4.7 out of 5 stars
    ·
    233 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    M

    MathWorks

    MathWorks Computer Vision Engineer

    Skills you'll gain: Computer Vision, Image Analysis, Anomaly Detection, Applied Machine Learning, Deep Learning, Image Quality, Artificial Neural Networks, Unsupervised Learning, Matlab, Application Deployment, PyTorch (Machine Learning Library), Machine Learning, Motion Graphics, Supervised Learning, Data Visualization, Automation, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Medical Imaging

    4.7
    Rating, 4.7 out of 5 stars
    ·
    341 reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Convolutional Neural Networks

    Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Artificial Neural Networks, Keras (Neural Network Library), Tensorflow, Applied Machine Learning, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Feature Engineering, Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    43K reviews

    Intermediate · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    M

    MathWorks

    Deep Learning for Computer Vision

    Skills you'll gain: Computer Vision, Anomaly Detection, Image Analysis, Matlab, Deep Learning, Artificial Neural Networks, Unsupervised Learning, Application Deployment, PyTorch (Machine Learning Library), Data Visualization, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Data Synthesis, Performance Tuning, Data Analysis, Classification And Regression Tree (CART), Data Validation, Medical Imaging

    4.9
    Rating, 4.9 out of 5 stars
    ·
    33 reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Introduction to Computer Vision

    Skills you'll gain: Image Analysis, Computer Vision, Deep Learning, Computer Graphics, Machine Learning Methods, Artificial Intelligence, Data Ethics, Microsoft Excel, Applied Machine Learning, Generative AI, Responsible AI, Linear Algebra, Data Manipulation, Feature Engineering, Probability Distribution

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    20 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free
    Free
    M

    Microsoft

    Build a computer vision app with Azure Cognitive Services

    Skills you'll gain: Application Programming Interface (API), Microsoft Azure, Computer Vision, Artificial Intelligence and Machine Learning (AI/ML), User Accounts, Image Analysis, Artificial Intelligence, Cloud Solutions, Cloud Computing, Software Development

    4.5
    Rating, 4.5 out of 5 stars
    ·
    449 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Deep Learning

    Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Tensorflow, Generative AI, Supervised Learning, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Keras (Neural Network Library), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, MLOps (Machine Learning Operations), Debugging, Performance Tuning, Python Programming, Data-Driven Decision-Making

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    147K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    M

    MathWorks

    Computer Vision for Engineering and Science

    Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Matlab, Applied Machine Learning, Machine Learning, Motion Graphics, Supervised Learning, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Visualization (Computer Graphics), Geospatial Information and Technology, Data Integration, Medical Imaging, Data Validation, Estimation, Machine Learning Methods, Performance Tuning, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    90 reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Preview
    Preview
    U

    University at Buffalo

    Computer Vision Basics

    Skills you'll gain: Computer Vision, Image Analysis, Computer Graphics, Visualization (Computer Graphics), Digital Design, Artificial Intelligence, Applied Machine Learning, Computer Programming, Matlab, Algorithms, Calculus, Probability & Statistics

    4.2
    Rating, 4.2 out of 5 stars
    ·
    1.8K reviews

    Intermediate · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular computer vision courses

  • Introduction to Computer Vision and Image Processing: IBM
  • Advanced Computer Vision with TensorFlow: DeepLearning.AI
  • Computer Vision: University of Colorado Boulder
  • First Principles of Computer Vision: Columbia University
  • MathWorks Computer Vision Engineer: MathWorks
  • Convolutional Neural Networks: DeepLearning.AI
  • Deep Learning for Computer Vision: MathWorks
  • Introduction to Computer Vision: University of Colorado Boulder
  • Build a computer vision app with Azure Cognitive Services: Microsoft
  • Deep Learning: DeepLearning.AI

Skills you can learn in Software Development

Programming Language (34)
Google (25)
Computer Program (21)
Software Testing (21)
Web (19)
Google Cloud Platform (18)
Application Programming Interfaces (17)
Data Structure (16)
Problem Solving (14)
Object-oriented Programming (13)
Kubernetes (10)
List & Label (10)

Frequently Asked Questions about Computer Vision

Computer vision is a field of artificial intelligence that enables computers to interpret and understand visual information from the world. It involves the development of algorithms and models that allow machines to process images and videos, recognize objects, and make decisions based on visual data. The importance of computer vision lies in its wide-ranging applications across various industries, including healthcare, automotive, security, and entertainment. By automating visual tasks, computer vision enhances efficiency, accuracy, and the ability to analyze large datasets, ultimately driving innovation and improving decision-making.‎

A career in computer vision can lead to various job opportunities, including roles such as computer vision engineer, machine learning engineer, data scientist, and research scientist. These positions are in high demand as organizations increasingly rely on visual data analysis for applications like autonomous vehicles, facial recognition systems, and augmented reality. Additionally, professionals in this field may work in sectors like robotics, healthcare imaging, and surveillance, where the ability to interpret visual information is crucial.‎

To pursue a career in computer vision, you should focus on developing a strong foundation in several key skills. These include programming languages such as Python and C++, proficiency in machine learning and deep learning frameworks, and a solid understanding of image processing techniques. Familiarity with libraries like OpenCV and TensorFlow is also beneficial. Additionally, knowledge of mathematics, particularly linear algebra and calculus, is essential for understanding the algorithms that underpin computer vision technologies.‎

There are numerous online courses available for those interested in computer vision. Some of the best options include the Computer Vision Specialization, which covers fundamental concepts and advanced techniques, and the Deep Learning for Computer Vision Specialization, which focuses on applying deep learning methods to visual data. Additionally, the MathWorks Computer Vision Engineer Professional Certificate offers a comprehensive curriculum designed to equip learners with practical skills in this field.‎

Yes. You can start learning computer vision on Coursera for free in two ways:

  1. Preview the first module of many computer vision courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in computer vision, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn computer vision effectively, start by building a solid foundation in programming and mathematics. Enroll in introductory courses that cover the basics of computer vision, such as the Computer Vision Basics course. As you progress, explore more advanced topics and practical applications through specialized courses. Engage in hands-on projects to apply your knowledge, and consider collaborating with peers or joining online communities to enhance your learning experience.‎

Typical topics covered in computer vision courses include image processing techniques, feature extraction, object detection, image segmentation, and the use of convolutional neural networks (CNNs). Courses may also explore advanced topics such as 3D vision, motion analysis, and the integration of computer vision with other AI technologies. By studying these areas, you will gain a comprehensive understanding of how to analyze and interpret visual data.‎

For training and upskilling employees in computer vision, courses like the Deep Learning for Computer Vision Specialization and the First Principles of Computer Vision Specialization are excellent choices. These programs provide structured learning paths that cover both foundational concepts and advanced techniques, making them suitable for professionals looking to enhance their skills and apply computer vision in their work.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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