Operate Ollama through the CLI and API with explicit installed, loaded, service, context, memory, residency, and troubleshooting checks.
Running Models with Ollama is an AcademAI beginner course in the Ollama Local AI Lab path for learners who want practical AI capability instead of passive tool exposure. It belongs to the Ollama Local AI Lab Training topic hub. The course includes 5 modules and an estimated workload of 3-4 hours. Start with the free AI Fluency foundation course before checkout; paid membership unlocks full access to this course and the broader catalog. The course is designed for Hands-on learners, analysts, support operators, and builders who need dependable model-running habits before customization or integration.. Learners should expect prerequisites such as Ollama 101 recommended. Core outcomes include Distinguish installed model state, loaded model state, Ollama service state, and session input.; Use exact model tags and CLI evidence to make repeated runs comparable.; Set context and model residency deliberately, including immediate unload with keep_alive: 0.. AcademAI course material is source-informed by public provider documentation where relevant, but the lessons, exercises, scenario mastery tests, and completion certificates are independently written by AcademAI and are not official provider certifications.
Hands-on learners, analysts, support operators, and builders who need dependable model-running habits before customization or integration.
Source-informed by Ollama's official documentation; AcademAI lessons, exercises, and scenario checks are original.
AcademAI certificates show independent course completion and are not official Ollama credentials.
This course is part of Ollama Local AI Lab Training, AcademAI's crawlable guide to the audience, outcomes, prerequisites, source policy, and recommended course sequence for this topic.
Installed models, loaded models, the Ollama service, ollama ps, and controlled stops
Exact tags, model metadata, fixed prompts, and comparison notes
Context length, memory pressure, keep_alive durations, and immediate unload
Version, model, command, service, process, log, hardware, and input evidence
Repeatable start, inspect, test, stop, update, and escalation routines
After completing the modules, pass a realistic scenario test to qualify for an AcademAI completion certificate.
Take scenario test