Deep Learning Architectures — Advanced Architectures and Generative Modeling | Computer Science Online Tutorial

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Deep Learning Architectures

A self-paced online tutorial session on advanced architectures and generative modeling, part of the Deep Learning Architectures track. Work through the topics below, then reach out any time if you'd like a live walkthrough.

Estimated session length: 9 hours Format: Online, self-paced

What this tutorial covers

  • 01Autoencoders
  • 02Variational Autoencoders (VAE)
  • 03Generative Adversarial Networks (GANs)
  • 04Transformer Models
  • 05Attention Mechanisms - applications of generative modelling Case studies
  • 06BERT
  • 07GPT-2- MuseNet
  • 08ProGAN
  • 09Sagan
  • 10BigGAN
  • 11StyleGAN
  • 12AI Art
  • 13AI Music

How to use this session

Read through each topic in order — they build on one another. Keep a notes document open and try to restate each concept in your own words before moving to the next one; that single habit does more for retention than re-reading ever will.

If any topic above needs a deeper explanation, a worked example, or a live session with an instructor, get in touch using the details below and we'll set up a time that works for you.

Need help with this topic?

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