Tool or Technology
TT0056

Mastering Ollama

Advanced Local AI, RAG, Agents & Enterprise Workflows

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

Programme Objectives

  • Develop advanced expertise in deploying, configuring, customising, and operating open AI models locally and through Ollama Cloud.
  • Build production-oriented AI applications using Ollama APIs, structured outputs, multimodal models, reasoning models, embeddings, RAG, and tool calling.
  • Architect agentic workflows that combine Ollama models with external functions, organisational knowledge, web information, and development tools.
  • Optimise model selection, context length, concurrency, hardware utilisation, inference performance, and application architecture for different workloads.
  • Apply security, privacy, governance, validation, monitoring, and human-review practices when deploying Ollama-based enterprise AI solutions.

Technology covered

OllamaOllama CLIOllama APIPython SDKJavaScript SDKLocal & Cloud ModelsModelfilesThinking ModelsVision ModelsStructured OutputsTool CallingEmbeddingsRetrieval-Augmented Generation (RAG)Web Search & Web FetchOpenAI-Compatible APIOllama Launch & Agentic Coding Integrations

Who should attend

  • AI / ML Engineers
  • Generative AI Engineers
  • Software Developers & Application Engineers
  • Backend Developers
  • Solution Architects
  • AI Solution Architects
  • Data Scientists
  • Data Engineers
  • Machine Learning Engineers
  • DevOps & Platform Engineers
  • Cloud & Infrastructure Engineers
  • MLOps Professionals
  • Enterprise Application Teams
  • AI Innovation & Digital Transformation Teams
  • Technical Leads & Engineering Managers

Prerequisites & Participant Readiness

  • Working knowledge of Python, JavaScript, or another application-development language
  • Basic understanding of Large Language Models and Generative AI
  • Familiarity with APIs, JSON, and command-line tools
  • Basic understanding of software-development and application-integration concepts
  • Familiarity with databases and information-retrieval concepts is beneficial for RAG modules
  • Basic knowledge of CPU, RAM, GPU, and application infrastructure is beneficial
  • Git and development-tool familiarity is recommended
  • Completion of shorter Ollama programmes is not required

TOC Modules

Concepts
  • Understanding Ollama as a platform for running and integrating open AI models
  • Understanding local inference versus cloud-hosted inference
  • Understanding model architecture, parameters, context windows, and hardware requirements
  • Understanding local-first AI architecture and enterprise deployment considerations
  • Understanding strengths and limitations of locally hosted models
Practical activities
  • Installing and validating Ollama on a development environment
  • Running multiple model families through the Ollama CLI
  • Comparing local and cloud model execution
  • Identifying suitable enterprise workloads for local AI

Scenarios

Private Enterprise Knowledge Assistant

Internal Documents → Embeddings → Vector Search → RAG → Local Ollama Model → Structured Response → Source Validation → Employee Answer

Participants build a local AI knowledge assistant that retrieves relevant organisational information and uses an Ollama-hosted model to produce grounded responses, improving internal research and knowledge-access efficiency while maintaining controlled data handling.

Intelligent Research & Operations Agent

Business Request → Ollama Reasoning Model → Local Knowledge + Web Search → Tool Selection → Enterprise Function → Structured Output → Human Validation → Business Action

Participants design an agentic workflow that combines local AI reasoning, organisational knowledge, current web information, external tools, and structured outputs to automate complex research and operational activities.

Related programmes

Continue with programmes from the same capability area.

Take the next step

Ready to make this programme work for your team?

Customise modules, duration and business scenarios for your team.

Instructor-ledVirtualHybrid

Designed around your roles, tools and real workflows.