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Computer Vision and Image Analysis


A deep dive into Computer Vision and Image Analysis using Python.

Enrollment is Closed View course

About this course

Computer Vision is the art of distilling actionable information from images.

In this hands-on course, we’ll learn about Image Analysis techniques using Python packages like PIL, Scikit-Image, OpenCV, and others. You’ll then explore machine learning for computer vision, including deep learning techniques for image classification, object detection, and semantic segmentation; using industry-standard machine learning frameworks like SciKit-Learn, Keras, and PyTorch.

What you'll learn

  • Explore, manipulate, and analyze images using Python packages for computer vision.
  • Implement image classification using classical machine learning and deep learning techniques.
  • Use data augmentation and transfer learning to create highly-effective convolutional neural networks (CNNs)
  • Go beyond image classification to use object detection and semantic segmentation models.

Prerequisites

  • Working knowledge of Python
  • Skills equivalent to the following courses
    • DAT263x: Introduction to AI
    • DAT236x: Deep Learning Explained

Meet the instructors

Graeme Malcolm

Graeme Malcolm

Senior Content Developer at Microsoft Learning Experiences

Graeme has been a trainer, consultant, and author for longer than he cares to remember, specializing in SQL Server and the Microsoft data platform. He is a Microsoft Certified Solutions Expert for the SQL Server Data Platform and Business Intelligence. After years of working with Microsoft as a partner and vendor, he now works in the Microsoft Learning Experiences team as a senior content developer, where he plans and creates content for developers and data professionals who want to get the best out of Microsoft technologies.

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