Computer Vision Essentials
Learn how machines see: image representation, CNNs, transformers, and where vision models fail.
intermediate · 45 minutes
This course builds an intermediate, conceptual foundation in modern computer vision. You will learn how images become numbers, how the core vision tasks differ, why convolutional networks and vision transformers work, and how transfer learning and multimodal models are used in practice. We finish with the failure modes every practitioner must anticipate: adversarial examples, distribution shift, and dataset bias.
What you'll learn
- How Images Become Numbers
- The Core Vision Tasks
- Convolutional Neural Networks
- Data Augmentation and Transfer Learning
- Vision Transformers and Multimodal Models
- Failure Modes and Robustness