Visual Recognition & Understanding

This course immerses learners in deep learning, the field of computer vision that deals with recognizing, identifying and understanding visual information from visual data, whether the information is from a single image or video sequence. Topics include object detection, face detection and recognition, and the progression of deep learning techniques.

This is the fourth course in the Computer Vision series that lays the groundwork necessary for designing sophisticated vision applications.

Course Duration: Approximately 4 weeks (4-5 hours of effort per week)

Learning Outcomes

  • Understand machine learning techniques used in computer vision
  • Classify letters, objects and scenes
  • Detect and recognize faces
  • Solve computer vision problems with deep learning

Intended Audience

Anyone curious about or interested in exploring the concepts of visual recognition and deep learning computer vision

Prerequisites

  • Basic programming skills & experience, specifically in MATLAB
  • Familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
  • Highly recommended that learners take the Deep Learning Onramp course

Credential Opportunities

  • Continuing Education Units (CEUs): TCIE grants 0.1 CEUs upon successful completion of this course for a fee of $25.
  • Professional Development Hours (PDHs): TCIE grants 1 PDH upon successful completion of this course for a fee of $25.   

For either a CEU or PDH, a learner must complete a request form. The process entails providing proof of the learner’s Verified Certificate (VC) issued by Coursera. A VC indicates a learner has completed a course with a passing score (he/she does not receive a letter grade). CEUs and PDHs are eligible for those earning a certificate on November 11, 2019 or later.