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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

    • U

      UNSW Sydney (The University of New South Wales)

      Remote Sensing Image Acquisition, Analysis and Applications

      Skills you'll gain: Image Analysis, Unsupervised Learning, Geospatial Information and Technology, Geospatial Mapping, Computer Vision, Feature Engineering, Spatial Analysis, Machine Learning, Dimensionality Reduction, Deep Learning, Supervised Learning, Probability & Statistics, Artificial Neural Networks

      4.7
      Rating, 4.7 out of 5 stars
      ·
      167 reviews

      Intermediate · Course · 3 - 6 Months

    • S

      Stanford University

      Probabilistic Graphical Models 3: Learning

      Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Markov Model, Machine Learning, Statistical Modeling, Network Analysis, Probability Distribution, Statistical Methods, Probability & Statistics, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      303 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Linux System Programming and Introduction to Buildroot

      Skills you'll gain: System Programming, Embedded Systems, Linux, Linux Commands, Unix, Operating Systems, Shell Script, File Systems, OS Process Management, Build Tools, C and C++, Debugging

      4.3
      Rating, 4.3 out of 5 stars
      ·
      132 reviews

      Advanced · Course · 1 - 4 Weeks

    • N

      Northwestern University

      Modern Robotics, Course 2: Robot Kinematics

      Skills you'll gain: Mathematical Modeling, Machine Controls, Automation Engineering, Engineering Calculations, Applied Mathematics, Engineering Analysis, Mechanics, Computational Logic, Simulation and Simulation Software, Virtual Environment, Torque (Physics), Numerical Analysis, Linear Algebra, Trigonometry, Control Systems

      4.9
      Rating, 4.9 out of 5 stars
      ·
      295 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Relational Database Design

      Skills you'll gain: Database Design, Database Management Systems, Relational Databases, Database Management, Database Architecture and Administration, Databases, Data Modeling, Data Integrity, Dependency Analysis, Technical Communication

      4.6
      Rating, 4.6 out of 5 stars
      ·
      294 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Codio

      Unix and Bash for Beginners

      Skills you'll gain: Package and Software Management, User Accounts, Unix Commands, Unix, Bash (Scripting Language), Command-Line Interface, Kubernetes, Git (Version Control System), GitHub, OS Process Management, Version Control, Firewall, Docker (Software), Containerization, Network Monitoring, Unix Shell, TCP/IP, Application Deployment, Data Storage, Network Protocols

      4
      Rating, 4 out of 5 stars
      ·
      99 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      Universitat Autònoma de Barcelona

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

      Skills you'll gain: Image Analysis, Computer Vision, Applied Machine Learning, Artificial Neural Networks, Deep Learning, Feature Engineering, Supervised Learning, Machine Learning Algorithms

      4.3
      Rating, 4.3 out of 5 stars
      ·
      79 reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Introduction to Machine Learning: Supervised Learning

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Decision Tree Learning, Scikit Learn (Machine Learning Library), Matplotlib, Random Forest Algorithm, Machine Learning, Predictive Modeling, Data Science, Python Programming, Classification And Regression Tree (CART), Mathematical Modeling, Applied Mathematics, Exploratory Data Analysis, Statistical Programming, Regression Analysis, Feature Engineering, Data Cleansing, Performance Tuning

      Build toward a degree

      3.4
      Rating, 3.4 out of 5 stars
      ·
      75 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of Geneva

      Simulation and modeling of natural processes

      Skills you'll gain: Simulations, Python Programming, Differential Equations, Numerical Analysis, Mathematical Modeling, Probability, Artificial Intelligence and Machine Learning (AI/ML), Computational Thinking, Visualization (Computer Graphics), Mechanics, Algorithms

      4.3
      Rating, 4.3 out of 5 stars
      ·
      398 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      S

      Sungkyunkwan University

      Fundamentals of CNNs and RNNs

      Skills you'll gain: Image Analysis, Computer Vision, Artificial Neural Networks, Natural Language Processing, Deep Learning, Network Model, Network Architecture

      4.4
      Rating, 4.4 out of 5 stars
      ·
      34 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado System

      Packet Switching Networks and Algorithms

      Skills you'll gain: Routing Protocols, Network Routing, TCP/IP, Network Protocols, Network Architecture, Network Performance Management, Computer Networking, OSI Models, Local Area Networks, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      448 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado System

      Cybersecurity for Business

      Skills you'll gain: Intrusion Detection and Prevention, Threat Detection, Open Web Application Security Project (OWASP), Incident Response, Penetration Testing, Computer Security Incident Management, Distributed Denial-Of-Service (DDoS) Attacks, Cybersecurity, Threat Management, Data Security, Authentications, Cyber Attacks, Security Testing, Cloud Security, Security Strategy, Computer Security Awareness Training, Malware Protection, Risk Management, Vulnerability Assessments, Enterprise Security

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Beginner · Specialization · 3 - 6 Months

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

    • Remote Sensing Image Acquisition, Analysis and Applications: UNSW Sydney (The University of New South Wales)
    • Probabilistic Graphical Models 3: Learning: Stanford University
    • Linux System Programming and Introduction to Buildroot: University of Colorado Boulder
    • Modern Robotics, Course 2: Robot Kinematics: Northwestern University
    • Relational Database Design: University of Colorado Boulder
    • Unix and Bash for Beginners: Codio
    • Clasificación de imágenes: ¿cómo reconocer el contenido de una imagen?: Universitat Autònoma de Barcelona
    • Introduction to Machine Learning: Supervised Learning: University of Colorado Boulder
    • Simulation and modeling of natural processes: University of Geneva
    • Fundamentals of CNNs and RNNs: Sungkyunkwan University

    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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