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Conceptual LLM Mechanics
Understand how language models work: from training to tokens to inference.
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Modules
7 total
How LLMs Are Created
ApplyUnderstand how pretraining, post-training, fixed weights, and inference-time context shape assistant behavior.
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2Token Sequences And Next-Token Prediction
ApplyUnderstand that LLMs process token sequences and generate one token at a time.
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3Transformers, Attention, And Context
ApplyBuild a conceptual model of transformers, attention, and context influence.
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4In-Context Learning And Prompt Influence
ApplyExplain why prompts, examples, and retrieved context influence behavior.
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5Sampling, Variability, And Evals
ApplyConnect temperature, sampling, and output variability to evals.
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6Inference Runtime: Prefill, Decode, KV Cache
ApplyConnect prefill, decode, KV cache, streaming, output length, latency, and cost.
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7Lab 1: AI-Native Mindset Challenge
LabBuild a support-ticket router and practice deterministic boundaries around probabilistic model output.
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