Introduction to Small Language Models

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About Course

By completing this course, learners will have the knowledge to:

  1. Explain what small language models are and how they differ from large models

  2. Identify appropriate and inappropriate use cases for SLMs

  3. Evaluate model outputs critically rather than accept them at face value

  4. Demonstrate controlled, reflective use of AI tools

  5. Articulate strengths and weaknesses of language models based on evidence

Course Content

Course Structure Overview
The course is organized into five modules, each culminating in a dual-track assignment that uses the assisted/unassisted framework. Each module includes: Conceptual material Guided interaction with AI tools One structured assignment with: - Assisted component - Unassisted component - Reflective comparison

Module 1: What Is a Language Model, Really?
This module establishes conceptual grounding. Its goal is not to make learners fluent in AI terminology, but to ensure they understand what language models actually do, what they do not do, and why their outputs can be simultaneously impressive and misleading. This module also introduces the core pedagogical pattern of the course: working with AI tools while remaining epistemically independent of them.

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