Computer Vision — image recognition, object detection, and visual AI

Categories: AI/ML, CSE
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About Course

The Computer Vision — Image Recognition, Object Detection, and Visual AI course equips learners with the skills to make computers “see” and interpret visual information.
From image classification and detection to real-time visual AI applications, this course covers everything you need to design intelligent systems that process and analyze images and videos.

Using Python, OpenCV, TensorFlow, and PyTorch, students will learn to build and deploy end-to-end Computer Vision models for real-world use cases such as face recognition, self-driving systems, and surveillance AI.

By the end, you’ll be able to develop, train, and optimize visual AI models for industry-grade applications.

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What Will You Learn?

  • Understand the foundations of digital image processing and visual data.
  • Implement image transformations and filtering using OpenCV.
  • Build convolutional neural networks (CNNs) for image classification.
  • Perform object detection using YOLO, SSD, and Faster R-CNN.
  • Work with real-time video streams and motion tracking.
  • Apply transfer learning with pre-trained vision models.
  • Deploy computer vision applications on the cloud or edge.
  • Learn best practices for AI ethics, bias, and privacy in visual systems.

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