Learn computer vision techniques, image processing, and neural networks for visual recognition tasks. Build real-world CV applications and master state-of-the-art architectures.
Dive deep into computer vision with this intensive 8-week course covering everything from basic image processing to advanced deep learning architectures. Learn to build real-world applications for image classification, object detection, and semantic segmentation.
You'll work with state-of-the-art frameworks like PyTorch and TensorFlow, implementing popular architectures like ResNet, YOLO, and U-Net. By the end, you'll have a portfolio of computer vision projects ready for industry use.
Real-time person and vehicle detection for security applications.
Classify medical images and detect anomalies using deep learning.
Lane detection and traffic sign recognition system.
Multi-label classification for fashion items and style recommendations.
Learn from computer vision experts
Computer Vision Lead at Tesla
Dr. Rodriguez leads the computer vision team at Tesla's Autopilot division and has 10+ years of experience in computer vision and autonomous systems. He has published 25+ papers and holds several patents in real-time object detection and semantic segmentation.