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Vision Transformers for Image Classification Hands-on

IntermediateGuided Project

Up your game in Image classification by using Vision Transformers to achieve remarkable performance, surpassing CNN-based methods, and delivering state-of-the-art results on large image datasets.

4.5 (73 Reviews)

Language

  • English

Topic

  • Computer Vision

Enrollment Count

  • 424

Skills You Will Learn

  • PyTorch, Python, Computer Vision, Deep Learning, Machine Learning

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 1 hour

Platform

  • SkillsNetwork

Last Update

  • September 29, 2025
About this Guided Project

Why you should do this guided project

 Vision Transformers (ViTs) are an exciting development in the field of computer vision, leveraging the Transformer architecture initially designed for natural language processing. The introduction of Transformers revolutionized NLP by effectively capturing long-range dependencies and achieving exceptional performance on tasks like machine translation and language understanding.
Now, this transformative architecture has been successfully applied to image classification tasks, yielding promising outcomes that often surpass the capabilities of traditional Convolutional Neural Networks (CNNs). This recent advancement in image classification using ViTs has created a significant buzz in the field. It is essential to familiarize yourself with the concept and knowledge surrounding ViTs in order to fully exploit their potential and stay up to date with the latest developments in this rapidly evolving domain.

A Look at the Project Ahead

This guided project offers a comprehensive introduction to the fundamentals of Computer Vision and Deep Learning, providing users with a strong understanding of key concepts. By completing this project, participants will:
  • Develop a solid grasp of the principles and workings of vision transformers.
  • Acquire the skills to seamlessly integrate vision transformers into image classification tasks.

What You'll Need

You just need a web browser!  Basic Python programming knowledge is recommended but it is not required. Everything else is provided to you via the IBM Skills Network Labs environment, where you will have access to the Cloud IDE and Python runtimes that we offer as part of the IBM Skills Network Labs environment. Remember that the IBM Skills Network Labs environment comes with many things pre-installed (e.g. Docker) to save them the hassle of setting everything up. Also note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.

Skills You'll Learn

  1. PyTorch: In this guided project, you will work with the PyTorch library to build and train a vision transformer specifically for image classification tasks. By leveraging the power of PyTorch, you will develop an efficient and accurate model to classify images effectively.
  2. Vision Transformers: You will explore the concept of vision transformers to enhance the efficiency and accuracy of your image classification system. Additionally, you will learn about their implementation to further refine the model.

Instructors

Roodra Kanwar

Data Scientist at IBM

I am a data scientist by day, superhero by night. Psych! I wish I was that cool. Only the former part is true which is still pretty cool! I believe in constant learning and it is an essential part of being a productive data enthusiast. I am also pursuing my masters in computer science from Simon Fraser University specializing in Big Data. Moreover, knowledge is transfer learning (pun intended!) and what I have gained, I plan on reflecting it back to the data community.

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Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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