Introduction to Open and Local AI
About this course
This course helps learners understand why open and local AI matter now, especially as AI usage becomes more expensive, more automated, and more embedded in organizational workflows. Learners quickly experience running a local model for free using LM Studio, then build the technical literacy to compare open and closed models, choose appropriate models for real tasks, create a simple private AI workflow, and leave with a practical strategy for deciding when to use hosted, local, open, closed, or hybrid AI approaches.
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What you'll learn
- run a local AI model using LM Studio
- compare characteristics of open and closed AI models
- select appropriate models for specific use cases
- design a basic private AI workflow
- develop a strategy for choosing between hosted, local, open, closed, and hybrid AI solutions
Course objectives
- understand the cost and automation implications of AI deployment choices
- gain practical experience with free, locally hosted models
- build technical literacy around model evaluation and integration
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