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Learning path

Small Language Models

Skill Level
Fundamentals
Duration 3 hours 10 minutes
Updated Aug 5, 2026

About this learning path

Small Language Models (SLMs) are reshaping enterprise AI by delivering targeted performance with lower cost and infrastructure demands than large models. This learning path explores what SLMs are, where they excel, how they compare to LLMs and APIs, and what it takes to deploy one, culminating in a hands-on lab.

Your instructors

Chirag Keshav PatelWorld Wide TechnologyTech Solutions Eng III, ATC / AI Proving Ground Team
Corey WanlessWorld Wide TechnologyPrincipal Solutions Architect
Craig KemmererWorld Wide TechnologyTech Solutions Arch II, ATC

Prerequisites

  1. Basic familiarity with AI/ML concepts (e.g., what a language model is)
  2. General understanding of enterprise IT infrastructure and on-premises vs. cloud deployment models
  3. No prior hands-on experience with SLMs required
  4. Basic command-line comfort recommended for the hands-on lab

What you'll learn

  1. What a Small Language Model (SLM) is and how it differs from a Large Language Model (LLM)
  2. The current SLM landscape and how the major open models compare
  3. Where SLMs excel and the top enterprise use cases driving adoption
  4. The business case for running SLMs on-premises
  5. How to decide between an SLM, an LLM, or an API-based approach for a given use case
  6. The infrastructure and architecture required to run an SLM in production
  7. How to deploy and query a Small Language Model hands-on
Learning path
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Small Language Models