Role-Based Programme
RB0378

Ollama for Information Technology

Build Private AI, RAG & Automated IT Workflows

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop functional proficiency in deploying and operating Ollama for local, cloud, and hybrid AI use cases within IT environments.
  • Build AI-assisted workflows for IT support, technical knowledge, incident analysis, troubleshooting, automation, and engineering productivity.
  • Implement embeddings, RAG, structured outputs, APIs, and tool calling for controlled enterprise IT solutions.
  • Evaluate models for capability, hardware requirements, context, latency, privacy, reliability, and operational suitability.
  • Apply security, access control, testing, monitoring, human approval, and governance to production-oriented AI workflows.

Tools covered

OllamaOllama Model LibraryLocal & Cloud ModelsOllama APIOpenAI-Compatible APIEmbeddingsStructured OutputsTool CallingWeb Search APIOllama LaunchCoding-Agent Integrations

Who should attend

  • IT Managers
  • IT Operations Professionals
  • System Administrators
  • Infrastructure Engineers
  • Application Support Engineers
  • DevOps Engineers
  • Platform Engineers
  • Cloud Engineers
  • Software Engineers
  • IT Service Management Professionals
  • Automation Engineers
  • Technical Support Engineers
  • AI / ML Platform Professionals
  • IT Team Leads

Prerequisites & Participant Readiness

  • Working understanding of IT systems, applications, infrastructure, or support operations
  • Basic familiarity with command-line tools, APIs, JSON, and HTTP concepts
  • Basic scripting or programming knowledge is beneficial
  • Familiarity with incidents, logs, technical documentation, and system troubleshooting
  • General understanding of generative AI and prompting is helpful
  • No previous Ollama course completion required

TOC Modules

Concepts
  • Understanding Ollama architecture, model execution, local inference, and cloud-model options
  • Mapping use cases across Support → Analyse → Automate → Integrate → Monitor
  • Understanding compute, memory, context-window, latency, and model-size considerations
Practical activities
  • Installing or configuring Ollama and validating the runtime environment
  • Mapping IT Workload → Model Requirement → Deployment Option → Operational Outcome

Scenarios

Internal IT Knowledge to Private Support Assistant

Approved Runbooks & Technical Documents → Embeddings → Semantic Retrieval → Ollama Model → Source-Grounded Response → Structured Troubleshooting Steps → Engineer Validation → Incident Resolution

Participants build a controlled IT-support workflow that retrieves relevant organisational knowledge and assists troubleshooting while keeping diagnosis and consequential technical actions under qualified IT ownership.

Incident Alert to Controlled Automated Response

Monitoring / Incident Input → Ollama API → Structured Classification → Technical Knowledge Retrieval → Tool Calling → Diagnostic Result → Human Approval → Remediation → Documentation

Participants combine Ollama APIs, structured outputs, RAG, and tool calling to create an intermediate IT-operations workflow with validation and approval checkpoints before system-impacting actions.

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