Computer Vision & Deep Learning
Build and deploy deep learning models for image classification, object detection, and visual AI applications using PyTorch and TensorFlow.
What You’ll Learn
- Convolutional neural networks (CNNs) from scratch
- Transfer learning with ResNet, EfficientNet, and Vision Transformers
- Object detection: YOLO, Faster R-CNN, and DETR
- Image segmentation with U-Net and Mask R-CNN
- OpenCV for real-time video processing
- Deploying vision models with ONNX and TensorRT
Requirements
- Python and basic ML knowledge required
Who This Course Is For
- AI/ML engineers building vision-based applications
- Researchers and engineers working with image and video data
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About this courseThis is a self-paced educational course. Completing it does not award a professional certification, license, degree or academic credit, and it does not count toward any licensing or continuing-education requirement. Exam-prep courses are independent study material: we are not affiliated with or endorsed by the exam provider, no exam voucher is included, and a certification is only awarded by the provider after you pass its exam. It makes no promise of employment, pay or exam results.