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Image Processing in Python

Updated 03/2026
Apply your Python skills to take on image data! From pre-processing to deep learning, you'll discover the many ways you can leverage image data.
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PythonData Manipulation12 hr17,433

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Track Description

Image Processing in Python

Much of the data in the world are formatted as images. Image processing has become a crucial skill to have in your data science toolbox. This track covers the fundamentals, from image pre-processing to deep learning. You'll begin with image enhancement and restoration and move on to biomedical images to analyze more complex image types, like MRI scans and X-rays. The track concludes with a course on convolutional neural nets, where you'll learn to build powerful deep learning image classifiers.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Image Processing in Python

    Learn to process, transform, and manipulate images at your will.

  • Project

    bonus

    Image Processing for Object Detection Models

    Building an image processing pipeline for data augmentation.

  • Course

    4

    Image Modeling with Keras

    Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Image Processing in Python
3 Courses
Track
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FAQs

Is this Track suitable for beginners?

Yes, this track is designed for beginners looking to gain expertise in image processing. The courses in the track start with fundamental concepts and progress in complexity step by step.

What is the programming language of this Track?

This track features courses in Python.

Which jobs will benefit from this Track?

This track will be beneficial to many roles, developers, data scientists, image analysts, and data engineers. It qualifies you for roles that focus on image analysis, restoration, and machine learning.

How will this Track prepare me for my career?

This track allows you to gain the skills needed to navigate image processing, enabling you to complete tasks with confidence and preparedness. You will be able to complete tasks like image compression, feature selection and classification, as well as harnessing the power of convolutional neural networks to create deep learning image classifiers.

How long does it take to complete this Track?

This track takes about 12 hours to complete as it consists of several courses.

What's the difference between a skill track and a career track?

A skill track is focused on teaching a method or technique, such as coding or machine learning. A career track, however, focuses on a range of skills and topics and is better suited for those looking to advance their career.

What datasets are used?

The datasets used in this track are sourced from real-world examples and are typically provided with each course.

What topics are covered in this Track?

This track covers topics from image enhancement and restoration to biomedical images and finally to convolutional neural networks. You will learn to build powerful deep learning image classifiers.

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