Course 9: Computer Vision


  • Math knowledge (Statistics and Probability, linear algebra, and calculus)
  • Knowledge of basic machine learning
  • Programming Knowledge – Python
  • Tensorflow or Pytorch knowledge

Who is this course for?

  • Students who complete the Tensorflow and/or Pytorch course and Basic AI and ML course and want to advance more.
  • Students who have not studied Computer Vision.
  • People who want to start their AI career specializing in Computer Vision field.

What you'll get after completeing this course:

Camera and Imaging

  • Image Formation
  • Image Sensing
  • Binary Images
  • Image Processing

Features and Boundaries

  • Edge Detection
  • Boundary Detection
  • SIFT Detector
  • Image Stitching
  • Face Detection

3D Reconstruction – Single Viewpoint

  • Getting Started: 3D Reconstruction – Single Viewpoint
  • Radiometry and Reflectance
  • Photometric Stereo
  • Shape from Shading
  • Depth from Defocus
  • Active Illumination Methods

3D Reconstruction – Multiple Viewpoints

  • Camera Calibration
  • Uncalibrated Stereo
  • Optical Flow
  • Structure from Motion

Visual Perception

  • Object Tracking
  • Image Segmentation
  • Appearance Matching
  • Neural Network

Do you have more questions?

Contact us

201 S. Grand Ave., 1st Floor New York City, NY 28020

Tell us a little about yourself and we’ll help with the rest. Our convenient online application tool only takes 10 minutes to complete.

After you submit your application, an admissions representative will contact you and will help you to complete the process.

Once you’ve completed your application and connected with an admissions representative, you’re ready to create your schedule.


Are you ready to begin this journey for yourself?