Master Large Language Models from an architect's perspective. This course gives you complete, decision-oriented knowledge of LLMs: how they really work, how to compare and choose models (proprietary and open-weight) by quality, cost, latency, licensing and trademarks, how to run open-source models yourself (serving, GPUs, quantization), and how to adapt models — fine-tuning (LoRA/QLoRA), small language models (SLMs), distillation and quantization. It finishes with reference architectures and a large interview-preparation section with worked system-design case studies.
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