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Computer Vision & Robotics Course

Computer Vision & Robotics Course
from 4 to 360h flexible workload
certificate valid in your country

What will I learn?

Gain hands-on expertise in constructing dependable mobile robots for warehouse environments. Master geometric vision principles, camera calibration, image formation techniques, and resilient feature extraction methods. Progress to advanced topics like detection, tracking, segmentation, and depth estimation. Additionally, excel in dataset creation, synthetic data generation, embedded GPU deployment, safety-oriented human detection, occupancy mapping, and integrated navigation systems.

Elevify advantages

Develop skills

  • Vision geometry and calibration: develop precise camera models suited for mobile robots.
  • Real-time detection: implement efficient YOLO-based models on embedded GPUs with safety measures.
  • Human tracking for safety: identify, follow, and assess people in proximity to robots.
  • Free-space and obstacle mapping: integrate RGB, depth, and lidar data into occupancy grids.
  • Dataset and domain adaptation: design, annotate, and tailor vision datasets for warehouse applications.

Suggested summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to change platforms... I'm grateful for everything you do, I've already recommended you to other people...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!
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Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.
André Felipe
André FelipePrompt Engineering Student

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