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Block 1: From text to numbers: tokens and meaning
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Chopping up the text: what a token is and why it matters
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From token to vector: a map of meanings
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Block 1 exam
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Block 2: Attention: how the model uses what it has in front of it
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Attending: every word looks at the others
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The context window: what it has in front of it and what it does not
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Block 2 exam
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Block 3: Training and adapting: what it learned, from where and up to when
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Learning to predict the next word
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From base model to assistant
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Block 3 exam
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Block 4: Generating: why it answers this way and why it sometimes makes things up
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Word by word: sampling, temperature and different answers
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Making things up with aplomb: where a false fact comes from
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Block 4 exam
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