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Course 4 of 4: Applied Artificial Intelligence – Computer Vision and Image Analysis
This course is part of the Advanced and Applied AI on Microsoft Azure QLMExpertFastTrack
Applied Artificial Intelligence: Computer Vision and Image Analysis
Master the significance of computer vision in AI and gain hands-on experience in image analysis.
Duration:
– 4 weeks
Weekly study:
– 5 hours
Included in an QLMExpertFastTrack:
– Course 4 of 4
Gain Machine Learning and AI Skills
This course is part of the Advanced and Applied AI on Microsoft Azure QLMExpertFastTrack, designed to enhance your AI and machine learning expertise and prepare you for relevant Microsoft microcredentials.
While humans can derive meaning from images effortlessly, computers need the aid of computer vision to interpret and extract information from visual data. This course delves into the essential techniques of Image Analysis and the pivotal role of computer vision in AI.
Explore the Evolution of Image Analysis
Learn about the development of Image Analysis to appreciate the background of this AI field. By the course’s end, you’ll be equipped to compare classical and deep learning object classification methods and apply these techniques to contemporary AI technologies.
Segment Images Using OpenCV and Microsoft Cognitive Toolkit
Gain practical experience with OpenCV and the Microsoft Cognitive Toolkit. Learn to segment images into meaningful components, reinforcing your understanding of computer vision.
You’ll explore implementing classical Image Analysis algorithms in OpenCV and learn to train a model for Semantic Segmentation using Transfer Learning and Microsoft ResNet. These are essential skills applicable to various computer vision tasks in AI.
What Topics Will You Cover?
– Current image segmentation techniques
– Image features and classical segmentation methods
– Object classification and detection
– Deep image segmentation
Prove You're Job Ready
Showcase your newly acquired, job-relevant skills with an industry-specific digital certificate for each course within your QLMExpertFastTrack.
– Stay current in your chosen field.
– Complete each course and pass assessments.
– Receive certificates validated by the educating organisation.
– Enhance your CV with impressive learning outcomes.
– Achieve your career aspirations.
Accreditation
Microsoft: This course is accredited by Microsoft.
Learning on This Course
Engage with other learners, share insights, and participate in active discussions throughout the course.
What Will You Achieve?
By the end of the course, you will be able to:
– Apply classical Image Analysis techniques, such as Edge Detection, Watershed, and Distance Transformation, as well as K-means Clustering, to segment a basic dataset.
– Implement classical Image Analysis algorithms using the OpenCV library.
– Compare classical and Deep Learning object classification techniques.
– Apply Microsoft ResNet, a deep Convolutional Neural Network (CNN), to object classification using the Microsoft Cognitive Toolkit.
Who Is the Course For?
This course is ideal for anyone with an interest in computer vision and a basic understanding of image processing.
Course Development
QLM has partnered with leading global technology companies to deliver cutting-edge digital skills training tailored for the modern workplace.
Course 4 of 4