Multimodal Applications with Ollama Training Course

The Advanced Ollama Model Debugging & Evaluation course offers a comprehensive deep dive into diagnosing, testing, and measuring model behaviour during local or private Ollama deployments.

This instructor-led live training, available either online or onsite, is designed for advanced AI engineers, ML Ops professionals, and QA practitioners seeking to guarantee the reliability, fidelity, and operational readiness of Ollama-based models in production environments.

Upon completion of this training, participants will be able to:

• Systematically debug Ollama-hosted models and reliably reproduce failure modes.
• Design and execute robust evaluation pipelines utilising both quantitative and qualitative metrics.
• Implement observability features (logs, traces, metrics) to monitor model health and detect drift.
• Automate testing, validation, and regression checks within CI/CD pipelines.

Course Format

• Interactive lectures and discussions.
• Hands-on labs and debugging exercises using Ollama deployments.
• Case studies, group troubleshooting sessions, and automation workshops.

Course Customisation Options

• To request bespoke training for this course, please contact us to arrange.

This instructor-led, live training in Australia (online or onsite) is targeted at advanced-level professionals looking to implement secure and efficient AI-driven workflows using Ollama.

Upon completion of this training, participants will be able to:

• Deploy and configure Ollama for private AI processing.
• Integrate AI models into secure enterprise workflows.
• Optimise AI performance while maintaining data privacy.
• Automate business processes with on-premise AI capabilities.
• Ensure compliance with enterprise security and governance policies.

This instructor-led, live training in Australia (online or on-site) is aimed at intermediate-level professionals who wish to deploy, optimise, and integrate LLMs using Ollama.

By the end of this training, participants will be able to:

• Set up and deploy LLMs using Ollama.
• Optimise AI models for performance and efficiency.
• Leverage GPU acceleration for improved inference speeds.
• Integrate Ollama into workflows and applications.
• Monitor and maintain AI model performance over time.

This instructor-led, live training in Australia (online or onsite) is designed for advanced-level professionals seeking to fine-tune and customise AI models on Ollama for enhanced performance and domain-specific applications.

Upon completing this training, participants will be able to:

• Establish an efficient environment for fine-tuning AI models on Ollama.
• Prepare datasets for supervised fine-tuning and reinforcement learning.
• Optimise AI models for performance, accuracy, and efficiency.
• Deploy customised models within production environments.
• Evaluate model improvements and ensure robustness.

This instructor-led, live training in Australia (online or onsite) is aimed at beginner-level professionals who wish to install, configure, and use Ollama for running AI models on their local machines.

By the end of this training, participants will be able to:

• Understand the fundamentals of Ollama and its capabilities.
• Set up Ollama for running local AI models.
• Deploy and interact with LLMs using Ollama.
• Optimise performance and resource usage for AI workloads.
• Explore use cases for local AI deployment in various industries.

Ollama is a platform enabling the local execution of large language and multimodal models, while also supporting robust secure deployment strategies.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals seeking to deploy Ollama with stringent data privacy and regulatory compliance measures.

Upon completion of this training, participants will be equipped to:

• Deploy Ollama securely within containerized and on-premises environments.
• Apply differential privacy techniques to protect sensitive data.
• Implement secure logging, monitoring, and auditing practices.
• Enforce data access controls that align with compliance requirements.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focusing on secure deployment patterns.
• Compliance-focused case studies and practical exercises.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Ollama is a lightweight platform designed for running large language models locally.

This instructor-led, live training, available either online or on-site, is tailored for intermediate-level finance practitioners and IT professionals who wish to implement, customise, and operationalise Ollama-based AI solutions within financial environments.

By completing this training, participants will gain the skills needed to:

• Deploy and configure Ollama for secure use in financial operations.
• Integrate local LLMs into analytical and reporting workflows.
• Adapt models to finance-specific terminology and tasks.
• Apply security, privacy, and compliance best practices.

Format of the Course

• Interactive lecture and discussion.
• Hands-on financial data exercises.
• Live-lab implementation of finance-focused scenarios.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Ollama is a lightweight platform for running large language models locally.

This instructor-led, live training (online or onsite) is aimed at intermediate-level healthcare practitioners and IT teams who wish to deploy, customize, and operationalize Ollama-based AI solutions within clinical and administrative environments.

Upon completing this training, participants will be able to:

• Install and configure Ollama for secure use in healthcare settings.
• Integrate local LLMs into clinical workflows and administrative processes.
• Customize models for healthcare-specific terminology and tasks.
• Apply best practices for privacy, security, and regulatory compliance.

Format of the Course

• Interactive lecture and discussion.
• Hands-on demonstrations and guided exercises.
• Practical implementation in a sandboxed healthcare simulation environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Ollama is an open-source tool designed for running large language models locally on both consumer and enterprise hardware. It simplifies model quantization, GPU allocation, and API serving into a single command-line interface, allowing organisations to self-host LLMs such as Llama, Mistral, and Qwen without sending prompts or data to OpenAI, Anthropic, or Google.

Ollama serves as a platform for executing large language and multimodal models locally, facilitating robust governance and responsible AI practices.

This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals seeking to embed fairness, transparency, and accountability into applications powered by Ollama.

Upon completion of this training, participants will be equipped to:

• Implement responsible AI principles within Ollama deployments.
• Execute content filtering and bias mitigation strategies.
• Design governance workflows to ensure AI alignment and auditability.
• Establish monitoring and reporting frameworks to support compliance.

Format of the Course

• Interactive lectures and discussions.
• Hands-on labs focused on designing governance workflows.
• Case studies and compliance-focused exercises.

Course Customization Options

• To arrange customized training for this course, please contact us.

Ollama serves as a platform for deploying large language and multimodal models locally and at scale.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced engineers looking to scale Ollama deployments for multi-user, high-throughput, and cost-efficient environments.

By the conclusion of this training, participants will be able to:

• Configure Ollama for multi-user and distributed workloads.
• Optimize GPU and CPU resource allocation.
• Implement strategies for autoscaling, batching, and reducing latency.
• Monitor and optimize infrastructure for performance and cost efficiency.

Course Format

• Interactive lectures and discussions.
• Hands-on labs for deployment and scaling.
• Practical optimization exercises conducted in live environments.

Customization Options

• To request customized training for this course, please contact us to arrange.

Ollama is a platform that allows you to run large language and multimodal models locally.

This instructor-led, live training (available online or on-site) is designed for intermediate-level practitioners who want to master prompt engineering techniques to optimise Ollama outputs.

By the end of this training, participants will be able to:

• Design effective prompts for diverse use cases.
• Apply techniques such as priming and chain-of-thought structuring.
• Implement prompt templates and context management strategies.
• Build multi-stage prompting pipelines for complex workflows.

Course Format

• Interactive lecture and discussion.
• Hands-on exercises with prompt design.
• Practical implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.