Computer Vision & Deep Learning for Robotics - Part of Post Diploma Certificate in Intelligent Autonomous Robotics (SDRE)

Training Provider: Ngee Ann Polytechnic
Course Reference: TGS-2023020850
S$318
Original: S$1,059
Save S$741

About This Course

You will learn:
Overview of Computer Vision,
OpenCV functions for Image Processing and Object Detection,
Convolutional Neural Networks (CNN),
Image Classification using Deep Learning,
Building CNN Models with Tensorflow 2,
Classifying Images using Keras available models,
Transfer Learning,
Object Detection using Deep Learning,
Object Detection Algorithms: SSD, YOLO, Faster R-CNN,
Real-Time Object Detection Application with Tensorflow 2,
Case Study: Person Re-Identification

What You'll Learn

Computer Vision & Deep Learning for Robotics - Part of Post Diploma Certificate in Intelligent Autonomous Robotics (SDRE) is a 30 hrs module. Learners will acquire computer vision and deep learning skills to solve real-word problems. The topics in this module are: Overview of Computer Vision, OpenCV Functions for Image Processing and Object Detection, Convolutional Neural Networks (CNN), Image Classification using Deep Learning, Building CNN Models with Tensorflow 2, Classifying images using Keras; Transfer Learning, Object Detection using Deep Learning, Object Detection Algorithms including SSD, YOLO and Faster R-CNN, Real-Time Object Detection Application with Tensorflow 2, and Case Study: Person Re-Identification.

Entry Requirements

At least a recognised local Polytechnic diploma in engineering or a degree in relevant areas.
Recognition of Prior Learning (RPL)
Applicants who do not meet the entry requirements may be considered for admission to the course based on evidence of at least 3 years of relevant working experience or supporting evidence of competency readiness.

Course Details

Duration 30 hours
Language English
Training Commitment Part Time
Total Enrolled New course
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Note: To apply for this course, visit the SkillsFuture website or contact the training provider directly.

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