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    • Computer Vision

    Computer Vision Courses Online

    Study computer vision for image processing applications. Learn about object detection, image recognition, and deep learning techniques.

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    Explore the Computer Vision Course Catalog

    • I

      IBM

      Introduction to Computer Vision and Image Processing

      Skills you'll gain: Computer Vision, Image Analysis, Artificial Neural Networks, IBM Cloud, Keras (Neural Network Library), Cloud Applications, Deep Learning, Tensorflow, Visualization (Computer Graphics), PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Computer Programming, Application Deployment, Augmented Reality, Machine Learning, Data Processing

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

      Beginner · Course · 1 - 3 Months

    • C

      Columbia University

      First Principles of Computer Vision

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

      4.7
      Rating, 4.7 out of 5 stars
      ·
      212 reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      MathWorks

      MathWorks Computer Vision Engineer

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

      4.7
      Rating, 4.7 out of 5 stars
      ·
      299 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Unlock Access to 10,000+ courses with a subscription.

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    • D

      DeepLearning.AI

      Advanced Computer Vision with TensorFlow

      Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Applied Machine Learning, Deep Learning, Feature Engineering, Artificial Neural Networks, Visualization (Computer Graphics), Data Processing, Network Architecture

      4.7
      Rating, 4.7 out of 5 stars
      ·
      520 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University at Buffalo

      Computer Vision Basics

      Skills you'll gain: Computer Vision, Image Analysis, Computer Graphics, Visualization (Computer Graphics), Data Processing, Digital Design, Artificial Intelligence, Matlab, Linear Algebra, Algorithms, Calculus, Probability & Statistics

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

      Intermediate · Course · 1 - 4 Weeks

    What brings you to Coursera today?

    • 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, Data Mapping, Artificial Intelligence and Machine Learning (AI/ML), Visualization (Computer Graphics), Geospatial Information and Technology, Feature Engineering, Medical Imaging, Machine Learning Algorithms, Data Validation, Geometric Dimensioning And Tolerancing, Performance Testing, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      85 reviews

      Intermediate · Specialization · 1 - 3 Months

    • M

      MathWorks

      Deep Learning for Computer Vision

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

      4.9
      Rating, 4.9 out of 5 stars
      ·
      20 reviews

      Beginner · Specialization · 1 - 3 Months

    • D

      DeepLearning.AI

      Convolutional Neural Networks

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Artificial Neural Networks, Tensorflow, Applied Machine Learning, PyTorch (Machine Learning Library), Artificial Intelligence, Data Processing, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      42K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      E

      Edge Impulse

      Computer Vision with Embedded Machine Learning

      Skills you'll gain: Computer Vision, Image Analysis, Artificial Neural Networks, Embedded Systems, Deep Learning, Data Ethics, Machine Learning, Artificial Intelligence, Python Programming, Data Collection, Performance Testing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      149 reviews

      Intermediate · 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

      4.4
      Rating, 4.4 out of 5 stars
      ·
      284 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • M

      MathWorks

      Object Tracking and Motion Detection with Computer Vision

      Skills you'll gain: Image Analysis, Computer Vision, Deep Learning, Matlab, Motion Graphics, Artificial Intelligence and Machine Learning (AI/ML), Visualization (Computer Graphics), Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      30 reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Microsoft

      Computer Vision in Microsoft Azure

      Skills you'll gain: Image Analysis, Computer Vision, Artificial Intelligence, Microsoft Azure, Applied Machine Learning, Data Processing, Natural Language Processing, Deep Learning, Application Programming Interface (API)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      104 reviews

      Beginner · Course · 1 - 4 Weeks

    What brings you to Coursera today?

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

      • Introduction to Computer Vision and Image Processing: IBM
      • First Principles of Computer Vision: Columbia University
      • MathWorks Computer Vision Engineer: MathWorks
      • Advanced Computer Vision with TensorFlow: DeepLearning.AI
      • Computer Vision Basics: University at Buffalo
      • Computer Vision for Engineering and Science: MathWorks
      • Deep Learning for Computer Vision: MathWorks
      • Convolutional Neural Networks: DeepLearning.AI
      • Computer Vision with Embedded Machine Learning: Edge Impulse
      • Build a computer vision app with Azure Cognitive Services: Microsoft

      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

      Coursera’s Computer Vision courses offer learners a deep dive into the technology and techniques used to interpret and process images and videos:

      • Fundamentals of image processing and analysis
      • Techniques for object detection, recognition, and tracking
      • Application of machine learning and deep learning models in computer vision
      • Use of popular computer vision libraries like OpenCV and TensorFlow
      • Skills for developing real-world computer vision applications, such as facial recognition and autonomous driving
      • Best practices for enhancing the performance and accuracy of vision systems‎

      Computer Vision courses are structured to accommodate learners with varying levels of expertise:

      • Beginners interested in computer vision can start with introductory courses that focus on basic concepts and tools.
      • Intermediate learners can expand their knowledge with courses on specific applications like image recognition or augmented reality.
      • Advanced students can explore complex topics involving neural networks and artificial intelligence as they apply to computer vision.‎

      Completing Computer Vision courses on Coursera enables learners to earn several types of credentials:

      • Professional certificates that demonstrate expertise in computer vision techniques
      • Specializations that cover detailed aspects of computer vision, from foundational skills to advanced applications
      • Certificates that are respected in the tech industry and can help propel your career in areas like research, development, and engineering ‎

      Skills gained from studying computer vision can lead to innovative and exciting career paths:

      • Computer Vision Engineer, developing algorithms and systems to interpret visual data
      • Robotics Engineer, integrating vision systems into robots for navigation and tasks
      • Software Developer, implementing computer vision functionalities in various applications
      • Research Scientist, pushing the boundaries of what's possible with AI and machine learning in vision
      • Product Manager, overseeing the development of products that rely on computer vision technology‎

      Looking to enhance your team's computer vision skills? Coursera provides tailored enterprise solutions for teams ranging of 5-125 employees. Our offerings include advanced analytics, customized learning paths, and collaborative tools. To explore our computer vision training options and make a purchase, please visit our Coursera for Teams page.‎

      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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