Learn Data Annotation Computer Vision and Object Detections with Hands-On Projects
InstructorMohammad RahishComidoc has tracked 3 coupons for this course since 2025, last checked 1 month, 9 days ago. On average, a new coupon appears roughly every 90 days.
| Coupon code | Discount | Added | Status | Lifetime |
|---|---|---|---|---|
| SPECIALOFFER | 33% off | Expired | 4d 22h | |
| APRILLEARN | 33% off | Expired | 4d 23h | |
| 1EB5BC7F6A10FB2917E7 | 100% off | Expired | ~4 daysRan full term |
The curriculum tracks the machine learning lifecycle from data preparation through training to deployment basics.
Instruction includes an image annotation assignment, a mini project, and a final machine learning project.
Editorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
This composite image illustrates computer vision object detection by showing green bounding boxes identifying plants, people, vehicles, and traffic signals across four distinct scenes.
This visualization demonstrates computer vision data annotation by overlaying colored bounding boxes and confidence score labels on a dataset of fruit images.
One signal suggests the curriculum lacks coverage of advanced tools like polygon or polyline in CVAT, as well as video, text, or audio annotation examples. Note that this review predates the displayed update date; while an update is noted, it does not prove these gaps were addressed.
One sampled review suggests that learners have noted low audio volume in specific sections and a tendency for the instructor to read directly from slides without additional explanation. This signal also predates the displayed update, leaving it uncertain if these issues persist.
Instruction on evaluation metrics like precision and recall may lack the depth of detailed examples required for full comprehension. This signal predates the displayed update, so its current relevance is uncertain.
The curriculum aligns well with the stated goal of introducing beginners to data annotation and machine learning fundamentals.