What You Need to Know Before
You Start
Starts 4 June 2026 11:14
Ends 4 June 2026
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Days
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Minutes
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Seconds
11 hours
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Paid Course
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Overview
Learn how computers process and understand image data, then harness the power of the latest Generative AI models to create new images.
Syllabus
- Introduction to Image Generation
- Computer Vision Fundamentals
- Image Generation and GANs
- Transformer-Based Computer Vision Models
- Diffusion Models
- Project: AI Photo Editing with Inpainting
In this lesson, you will define image generation and understand its relevance in AI and machine learning.
Learn how computers see images and perform key image processing techniques using classic image processing techniques such as image transformation, noise reduction, and more.
Explore the landscape of Gen AI tools for Computer Vision and learn how they are evaluated. Learn what a generative adversarial network is and how it is utilized to generate images.
In this lesson, we will be exploring Vision Transformers and the architecture that makes them work. Along the way we will explore Vision Transformers like DALL-E, DINO, and SAM.
Learn the fundamentals of transformers. Then, get hands-on with the creation of a diffusion algorithm and work with Huggingface Diffusers to generate and work with images.
In this project, you will utilize Generative AI to take a famous painting and swap out the background with an image generated by Stable Diffusion.
Taught by
Giacomo Vianello, Chuyi Shang, Annabel Ng, Derek Xu and Nathaniel Haynam
Subjects
Computer Science