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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

    • 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
      ·
      105 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Introduction to Computer Vision

      Skills you'll gain: Image Analysis, Computer Vision, Computer Graphics, Deep Learning, Data Ethics, Computational Thinking, Artificial Intelligence, Data Processing, Linear Algebra, Probability Distribution

      Build toward a degree

      4.4
      Rating, 4.4 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Deep Learning

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

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      146K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Deep Learning Applications for Computer Vision

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

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      87 reviews

      Intermediate · Course · 1 - 3 Months

    • M

      MathWorks

      Introduction to Computer Vision

      Skills you'll gain: Image Analysis, Computer Vision, Matlab, Data Mapping, Geospatial Information and Technology, Feature Engineering, Medical Imaging, Visualization (Computer Graphics), Applied Machine Learning, Geometric Dimensioning And Tolerancing, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      52 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      IBM Generative AI Engineering

      Skills you'll gain: Prompt Engineering, Generative AI, Data Wrangling, Large Language Modeling, Unit Testing, Supervised Learning, Feature Engineering, Keras (Neural Network Library), Deep Learning, ChatGPT, Natural Language Processing, Data Cleansing, Jupyter, Data Analysis, Unsupervised Learning, Data Manipulation, PyTorch (Machine Learning Library), Artificial Intelligence, Data Import/Export, Data Ethics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      86K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • G

      Google Cloud

      Computer Vision Fundamentals with Google Cloud

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Applied Machine Learning, Artificial Neural Networks, Deep Learning, Supervised Learning, Google Cloud Platform, Machine Learning Methods, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Small Data, Data Processing, Cloud API

      4.5
      Rating, 4.5 out of 5 stars
      ·
      543 reviews

      Advanced · Course · 1 - 3 Months

    • Status: New AI skills
      New AI skills
      G

      Google

      Google Cybersecurity

      Skills you'll gain: Threat Modeling, Network Security, Threat Management, Incident Response, Vulnerability Management, Computer Security Incident Management, Hardening, Intrusion Detection and Prevention, Cyber Threat Intelligence, Cyber Attacks, Cybersecurity, Network Protocols, Cloud Security, Vulnerability Assessments, Threat Detection, Bash (Scripting Language), Operating Systems, Security Controls, Debugging, Python Programming

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      51K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Supervised Learning, Feature Engineering, Plotly, Interactive Data Visualization, Jupyter, Data Literacy, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Unsupervised Learning, Generative AI, Pandas (Python Package), Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      143K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Full Stack Software Developer

      Skills you'll gain: Istio, Node.JS, Software Development Life Cycle, Kubernetes, Unit Testing, Cloud Computing Architecture, Server Side, Application Deployment, React Redux, Cloud Services, Django (Web Framework), Cloud-Native Computing, Object-Relational Mapping, Git (Version Control System), Full-Stack Web Development, HTML and CSS, Cloud Computing, Jupyter, Large Language Modeling, Interviewing Skills

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      55K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • M

      MathWorks

      Advanced Deep Learning Techniques for Computer Vision

      Skills you'll gain: Anomaly Detection, Image Analysis, Computer Vision, Matlab, Deep Learning, Applied Machine Learning, Application Deployment, PyTorch (Machine Learning Library), Data Synthesis, Medical Imaging

      4.9
      Rating, 4.9 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google

      Crash Course on Python

      Skills you'll gain: Programming Principles, Scripting, Python Programming, Computer Programming, Computational Thinking, Algorithms, Data Structures, Integrated Development Environments, Debugging, Development Environment

      4.8
      Rating, 4.8 out of 5 stars
      ·
      39K reviews

      Beginner · Course · 1 - 3 Months

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

    • Computer Vision in Microsoft Azure: Microsoft
    • Introduction to Computer Vision: University of Colorado Boulder
    • Deep Learning: DeepLearning.AI
    • Deep Learning Applications for Computer Vision: University of Colorado Boulder
    • Introduction to Computer Vision: MathWorks
    • IBM Generative AI Engineering: IBM
    • Computer Vision Fundamentals with Google Cloud: Google Cloud
    • Google Cybersecurity: Google
    • IBM Data Science: IBM
    • IBM Full Stack Software Developer: IBM

    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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