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Computer Vision and Image Analysis


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

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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