Role-Based Programme
RB0379

Ollama for Information Technology

Advanced Local AI, RAG, Agentic Automation & Enterprise Integration

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced proficiency in deploying, configuring, operating, and integrating Ollama across enterprise IT and software environments.
  • Architect private/local AI solutions using model management, APIs, embeddings, retrieval-augmented generation, structured outputs, vision, and tool calling.
  • Build reusable AI assistants and agentic workflows that interact safely with approved IT systems, technical data, knowledge repositories, and functions.
  • Optimise model selection, context length, hardware utilisation, runtime behaviour, troubleshooting, and integration patterns for realistic workloads.
  • Establish enterprise controls for model governance, access, credentials, sensitive data, tool permissions, validation, monitoring, and human approval.

Tools covered

OllamaOllama CLIOllama APIPython & JavaScript LibrariesLocal ModelsOllama Cloud ModelsModelfileStructured OutputsEmbeddingsVision ModelsTool CallingAgent LoopsWeb Search & Web Fetch APIsOpenAI-Compatible APIModel Management & Runtime Controls

Who should attend

  • IT Managers
  • AI / Solution Architects
  • Software Engineers
  • Application Developers
  • DevOps Engineers
  • Platform Engineers
  • Cloud Engineers
  • System Administrators
  • Infrastructure Engineers
  • IT Operations Professionals
  • Application Support Engineers
  • Technical Leads
  • Automation Engineers
  • Enterprise AI Engineering Professionals

Prerequisites & Participant Readiness

  • Working understanding of enterprise IT, software-development, or infrastructure environments
  • Familiarity with command-line tools, APIs, JSON, and application integration
  • Basic programming or scripting knowledge in Python, JavaScript, or a similar language
  • Basic understanding of containers, networking, databases, or cloud concepts is recommended
  • Familiarity with generative AI and LLM concepts is helpful
  • No requirement to complete shorter Ollama courses
  • Suitable compute resources should be available for selected local models; hardware requirements vary significantly by model size, context length, and workload

TOC Modules

Concepts
  • Understanding Ollama as a runtime and API environment for local and cloud-accessible AI models
  • Exploring models for chat, coding, reasoning, vision, and embeddings
  • Mapping Application → Ollama API → Model → Compute → Response
  • Comparing local execution with Ollama Cloud model usage for different IT requirements
Practical activities
  • Installing and validating Ollama in a controlled environment
  • Running and interacting with an initial model
  • Testing local API connectivity
  • Designing a reference enterprise Ollama deployment architecture

Scenarios

Enterprise IT Knowledge Assistant with Governed Actions

Runbooks + SOPs + Architecture Documents → Ollama Embeddings → Semantic Retrieval → Local LLM → Structured Response → Approved IT Tool Call → Human Confirmation → Action → Audit Record

Participants architect a private IT assistant that answers operational questions from approved technical knowledge and can invoke tightly controlled functions while maintaining source validation and human approval for consequential actions.

Incident Evidence to Agent-Assisted Resolution

Incident Alert → Logs + Screenshot + Technical Context → Ollama Agent → RAG / Web Research → Tool Calls → Root-Cause Hypotheses → Engineer Validation → Controlled Remediation → Resolution Documentation

Participants combine multimodal analysis, technical knowledge retrieval, current research, agent loops, and approved functions to support incident investigation while retaining diagnosis, production changes, and final remediation decisions with qualified IT professionals.

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