Explore the fascinating world of generative models with a deep focus on diffusion models for high-quality image generation. You’ll begin by mastering the core principles of diffusion and then advance to the architectures that power modern text-to-image systems. Learn how these models transform random noise into stunning visuals through forward and reverse processes, and discover optimization techniques using loss functions and training strategies.
How to Build a Diffusion Model - An Introduction
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您将学到什么
Explain the core concepts of diffusion models and their role in the generative AI landscape.
Design diffusion models from scratch using effective training strategies.
Build text-to-image generation systems leveraging advanced techniques.
Evaluate model performance using real-world metrics.
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作业
7 项作业
授课语言：英语（English）
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该课程共有3个模块
Explore the fundamentals of deep learning and generative models. Understand the diffusion process, its types, and applications in AI.
涵盖的内容
7个视频3篇阅读材料3个作业
Learn the architecture and mechanics of diffusion models. Dive into forward/reverse passes, loss functions, and training strategies.
涵盖的内容
29个视频5篇阅读材料4个作业5个非评分实验室
Build end-to-end text-to-image systems. Cover data preparation, model construction, training, evaluation, and hands-on labs.
涵盖的内容
1个视频3篇阅读材料1次同伴评审
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常见问题
It’s a practical introduction to diffusion models—one of the most powerful techniques in generative AI for image creation.
You’ll be able to build, train, and evaluate diffusion models, including text-to-image systems.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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