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Module 05Intermediate
LLMs
Understand how Large Language Models process data, transformer architecture, inference parameters, and selection strategies.
Module Completion0 of 5 Topics (0%)
Topic Lessons (5)
1.
The Conceptual Story
20m •How LLMs process data: tokens, embeddings, attention mechanisms, and transformer architecture.
20m
2.
Inference Controls
15m •Temperature, top-p, context windows, and reasoning vs. fast models.
15m
3.
Core Limitations
15m •Hallucinations, latency, cost overheads, and knowledge cutoffs.
15m
4.
The Model Landscape
15m •Open-source vs. closed-source, benchmarks, and multi-model routing.
15m
5.
Selection Strategy
20m •Choosing model types based on cost, speed, task complexity, and security.
20m