Getting Started with Ollama: Running Local AI Models Training Course

Advanced Ollama Model Debugging & Evaluation is an intensive course dedicated to diagnosing, testing, and measuring model behaviour within local or private Ollama deployments.

This instructor-led live training (delivered online or onsite) caters to advanced-level AI engineers, ML Ops professionals, and QA practitioners aiming to guarantee the reliability, fidelity, and operational readiness of Ollama-based models in production environments.

Upon completing 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 integrated into 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.

Customisation Options

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

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

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

• Deploy and configure Ollama for private AI processing.
• Integrate AI models into secure enterprise workflows.
• Optimize 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 Malaysia (online or onsite) 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 Malaysia (online or onsite) is aimed at advanced-level professionals who wish to fine-tune and customise AI models on Ollama for enhanced performance and domain-specific applications.

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

• Set up 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 in production environments.
• Evaluate model improvements and ensure robustness.

Ollama serves as a platform for running and fine-tuning large language and multimodal models directly on your local machine.

Delivered via instructor-led live training (available online or onsite), this programme is tailored for advanced-level machine learning engineers, AI researchers, and product developers seeking to construct and deploy multimodal applications leveraging Ollama.

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

• Deploy and operate multimodal models using Ollama.
• Combine text, image, and audio inputs for practical, real-world solutions.
• Develop systems for document comprehension and visual question answering.
• Create multimodal agents capable of reasoning across different data modalities.

Training Format

• Interactive lectures and discussions.
• Practical exercises using real multimodal datasets.
• Live laboratory sessions for implementing multimodal pipelines with Ollama.

Customization Options

• For a tailored training experience, please reach out to us to arrange your custom session.

Ollama is a platform that enables the local execution of large language and multimodal models while supporting secure deployment strategies.

This instructor-led live training, available online or on-site, targets intermediate-level professionals aiming to deploy Ollama with robust data privacy and regulatory compliance measures.

Upon completing this training, participants will be able 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 focused on secure deployment patterns.
• Compliance-focused case studies and practical exercises.

Customization Options

• To request 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 online or onsite) targets intermediate-level finance professionals and IT staff looking to implement, customize, and operationalize Ollama-based AI solutions within financial environments.

Upon completing this training, participants will acquire the skills necessary to:

• Deploy and configure Ollama for secure application 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.

Course Format

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

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 session (available online or on-site) is designed for intermediate-level healthcare practitioners and IT teams seeking to deploy, customize, and operationalize Ollama-based AI solutions within clinical and administrative settings.

Upon completing this training, participants will be able to:

• Install and configure Ollama to ensure secure usage in healthcare environments.
• Integrate local Large Language Models (LLMs) into clinical workflows and administrative processes.
• Customize models to handle healthcare-specific terminology and tasks.
• Apply best practices for privacy, security, and regulatory compliance.

Course Format

• Interactive lectures and discussions.
• Hands-on demonstrations and guided exercises.
• Practical implementation within a sandboxed healthcare simulation environment.

Customization Options

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

Ollama is an open-source utility designed to run large language models locally on both consumer and enterprise-grade hardware. It streamlines model quantization, GPU resource allocation, and API serving into a single command-line interface, allowing organisations to self-host models such as Llama, Mistral, and Qwen without transmitting prompts or data to external providers like OpenAI, Anthropic, or Google.

Ollama serves as a platform for executing large language and multimodal models on local infrastructure, with a strong emphasis on supporting governance frameworks and responsible AI practices.

Offered as an instructor-led live training session—available either online or onsite—this course targets intermediate to advanced professionals who aim to embed fairness, transparency, and accountability into applications powered by Ollama.

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

• Integrate responsible AI principles into Ollama deployments.
• Deploy strategies for content filtering and bias mitigation.
• Architect governance workflows that ensure AI alignment and auditability.
• Set up monitoring and reporting frameworks to meet compliance requirements.

Course Format

• Engaging interactive lectures and discussions.
• Practical labs focused on designing governance workflows.
• Real-world case studies and exercises centered on compliance.

Customization Options

• For organizations seeking tailored training for this course, please reach out to us to arrange specific requirements.

Ollama is a platform designed for running large language and multimodal models locally and at scale.

This instructor-led live training (available online or on-site) targets intermediate to advanced engineers who aim 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.
• Optimise GPU and CPU resource allocation.
• Implement strategies for autoscaling, batching, and latency reduction.
• Monitor and optimise infrastructure for performance and cost efficiency.

Course Format

• Interactive lecture and discussion.
• Hands-on deployment and scaling labs.
• Practical optimisation exercises in live environments.

Course Customisation Options

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

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

This instructor-led live training, available either online or onsite, is designed for intermediate-level practitioners who want to master prompt engineering techniques to enhance Ollama outputs.

Upon completing this training, participants will be able to:

• Craft effective prompts tailored to diverse use cases.
• Apply methods such as priming and chain-of-thought structuring.
• Implement prompt templates and strategies for managing context.
• Develop multi-stage prompting pipelines for complex workflows.

Course Format

• Interactive lectures and discussions.
• Practical exercises in prompt design.
• Hands-on implementation in a live-lab setting.

Customization Options

• For customized training on this course, please contact us to arrange a session.