Become a Wizard of all the latest Computer Vision tools that exist out there. Detect anything and create powerful apps.
InstructorHadelin de PontevesLessons follow a pattern of teaching technical intuition followed by practical application steps, often concluding with quizzes.
Specific modules include dedicated homework challenges that provide instructions and video solutions for practical application.
Editorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
This image demonstrates computer vision object detection by displaying a green bounding box and label around a horse in an outdoor scene.
This scene demonstrates object tracking on moving subjects, showing how computer vision models can identify and follow animals like horses in real-time video sequences.
Learner signals from early 2025 suggest that code in several modules fails due to deprecated PyTorch implementations; while the course has a more recent update label, it is uncertain if these issues were addressed.
One signal suggests difficulty setting up a functional development environment; this signal predates the displayed course update, and while the update may have addressed it, the update label does not prove that it was corrected.
The curriculum aligns with the stated goals of learning computer vision through Python and OpenCV.
