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MICRO-COURSE

Generative AI & Foundation Models

Generative AI & Foundation Models: 9 short lessons, one for each concept. Generative versus discriminative modeling, autoregressive models, diffusion models, generative adversarial networks, variational autoencoders, foundation models, language models, vision-language models, and text, image, audio

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01 / WATCH

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02 / UNDERSTAND

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Generative versus discriminative modeling, autoregressive models, diffusion models, generative adversarial networks, variational autoencoders, foundation models, language models, vision-language models, and text, image, audio, and video generation.

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01

Concept scope

Generative AI & Foundation Models: 9 short lessons, one for each concept. Generative versus discriminative modeling, autoregressive models, diffusion models, generative adversarial networks, variational autoencoders, foundation models, language models, vision-language models, and text, image, audio

03 / TRY IT

Prepare a focused example

  1. Choose one question about Generative AI & Foundation Models that you want to answer.
  2. Write down a small example, its inputs or starting point, and the result you expect.
  3. Explain your reasoning and note what you would like reviewed in a live or 1:1 session.
Keep your work

A short example, reasoning and an open question

Check your understanding

  • Explain the concept in your own words and identify where it fits in the subject.
  • Show one small example, the expected result and the reasoning behind it.
  • Record one limitation or edge case and a question to discuss with a mentor.
04 / LEARN WITH HELP

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