Coursera Course Description
Prepare for a career in the rapidly expanding field of computer vision. The ability to extract meaningful information from visual data is crucial for efficiently developing smart monitoring systems, enhancing medical diagnostics, and powering the next generation of autonomous vehicles. This program is designed to transform those with little or no prior image data experience into proficient computer vision practitioners by completing several hands-on projects with real-world applications.
By the end of the program, you will have the skills necessary to automate image processing tasks, detect and track motion, train deep learning models for image classification and object detection tasks, and implement advanced deep learning techniques like data augmentation and AI-assisted annotation. Possessing these skills will prepare you to keep pace with modern systems, which increasingly incorporate cameras into their designs.
Throughout the program, you will use MATLAB, an industry-standard platform known for its user-friendly interface and robust functions that simplify complex algorithms. The intuitive apps and functions mean that you don’t need to be a programmer or math expert to achieve success. You will leverage MATLAB capabilities to rapidly prototype and iterate on solutions, giving you a competitive edge in the job market and the confidence to push the boundaries of what’s possible in computer vision and deep learning.
Applied Learning Project
Detecting anomalies in medical images for further investigation
This professional certificate includes several real-world projects to ensure you are industry-ready.
Measuring Antarctic ice melt by analyzing satellite images
Detecting and tracking cars on a busy highway
Examining the Martian surface by stitching together images from a Mars rover
Detecting and classifying the letters of the ASL alphabet for accessible communication
Identifying and locating parking signs for automated parking assistance
ENROLLMENT
To enroll click to course , click HERE
