Introduction to Computer Vision and Image Processing
- 4.5
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Approx. 21 hours to complete
Course Summary
This course provides an introduction to computer vision and its applications using the Watson AI platform and OpenCV library. Students will learn how to build computer vision applications for image and video analysis.Key Learning Points
- Understand the basics of computer vision and its applications
- Learn how to use OpenCV and the Watson AI platform for computer vision
- Build computer vision applications for image and video analysis
Job Positions & Salaries of people who have taken this course might have
- USA: $111,000
- India: ₹1,200,000
- Spain: €45,000
- USA: $111,000
- India: ₹1,200,000
- Spain: €45,000
- USA: $120,000
- India: ₹1,500,000
- Spain: €50,000
- USA: $111,000
- India: ₹1,200,000
- Spain: €45,000
- USA: $120,000
- India: ₹1,500,000
- Spain: €50,000
- USA: $135,000
- India: ₹2,000,000
- Spain: €60,000
Related Topics for further study
Learning Outcomes
- Understand the fundamentals of computer vision and its applications
- Learn how to use OpenCV and the Watson AI platform for computer vision
- Build computer vision applications for image and video analysis
Prerequisites or good to have knowledge before taking this course
- Basic programming knowledge in Python
- Familiarity with computer vision concepts
Course Difficulty Level
IntermediateCourse Format
- Online self-paced course
- Video lectures and coding exercises
Similar Courses
- Applied Computer Vision with TensorFlow
- Python for Computer Vision with OpenCV and Deep Learning
Related Education Paths
- IBM Watson AI Foundations for Developers Professional Certificate
- Deep Learning Specialization
- Machine Learning Engineer Nanodegree
Notable People in This Field
- Co-Director, Stanford Institute for Human-Centered Artificial Intelligence
- Founder, deeplearning.ai
Related Books
Description
Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries, such as self-driving cars, robotics, augmented reality, and much more. In this beginner-friendly course, you will understand computer vision and learn about its various applications across many industries.
Outline
- Introduction to Computer Vision
- Introduction to Computer Vision
- Applications of Computer Vision
- Recent Research in Computer Vision
- Brainstorming Your Own Applications
- Course Overview
- Articles
- Practice Assessment
- Graded Quiz: Overview of Computer Vision and its Applications
- Image Processing with OpenCV and Pillow
- What Is A Digital Image
- Manipulating Images
- Manipulating Images One Pixel At a Time
- Pixel Transformations
- Geometric Operations
- Spatial Operations in Image Processing
- Practice Assessment
- Graded Quiz: Image Processing
- Machine Learning Image Classification
- Introduction to Image Classification
- Image Classification with KNN
- Linear Classifiers
- Logistic Regression Training: Gradient Descent
- Mini-Batch Gradient Descent
- SoftMax and Multi-Class Classification
- Support Vector Machines
- Image Features
- Practice Assessment
- Graded Quiz: Image Classification
- Neural Networks and Deep Learning for Image Classification
- Neural Networks
- Fully Connected Neural Network Architecture
- Convolutional Networks
- CNN Architectures
- Practice Assessment
- Graded Quiz: Neural Networks
- Object Detection
- Object Detection
- Object Detection with Haar Cascade Classifier
- Object Detection with Deep Learning
- Practice Assessment
- Graded Quiz: Object Detection
- Project Case: Not Quite a Self-Driving Car - Traffic Sign Classification
Summary of User Reviews
Discover the world of computer vision with Watson and OpenCV through this comprehensive course on Coursera. Students have given high praise for the engaging content, practical exercises, and helpful instructors. One key aspect that many users appreciate is the real-world applications and examples provided throughout the course.Pros from User Reviews
- Engaging content that is easy to follow
- Practical exercises to apply concepts learned
- Helpful and knowledgeable instructors
- Real-world applications and examples provided
- Great introduction to computer vision
Cons from User Reviews
- Some users found the course challenging and time-consuming
- Limited focus on deep learning and advanced computer vision techniques
- Some users reported technical issues with the platform
- Course could benefit from more hands-on projects
- Not suitable for those without a basic understanding of programming
Aije Egwaikhide
4.5 Raiting
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