Getting Started with Ollama: Running Local AI Models Training Course

Advanced Ollama Model Debugging & Evaluation is an in-depth course designed to help participants diagnose, test, and measure the behavior of models when deployed locally or privately using Ollama.

This instructor-led, live training (available online or onsite) targets advanced-level AI engineers, ML Ops professionals, and QA practitioners who aim to ensure the reliability, accuracy, and operational readiness of Ollama-based models in production environments.

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

• Conduct systematic debugging of models hosted on Ollama and reliably reproduce failure scenarios.
• Create and execute robust evaluation pipelines using both quantitative and qualitative metrics.
• Implement observability features such as logs, traces, and metrics to monitor model health and detect drift.
• Integrate automated testing, validation, and regression checks into CI/CD pipelines.

Format of the Course

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

Course Customization Options

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

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

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

• Set up and deploy LLMs using Ollama.
• Optimize 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 Uzbekistan (online or onsite) is aimed at advanced-level professionals who wish to fine-tune and customize 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.
• Optimize AI models for performance, accuracy, and efficiency.
• Deploy customized models in production environments.
• Evaluate model improvements and ensure robustness.

Ollama is a platform that facilitates the local execution and fine-tuning of large language and multimodal models.

This instructor-led, live training (available online or on-site) is designed for advanced ML engineers, AI researchers, and product developers who aim to build and deploy multimodal applications using Ollama.

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

• Set up and run multimodal models with Ollama.
• Integrate text, image, and audio inputs for practical applications.
• Create systems for document understanding and visual question answering (QA).
• Develop multimodal agents capable of reasoning across different types of data.

Format of the Course

• Interactive lectures and discussions.
• Hands-on practice with real multimodal datasets.
• Live-lab implementation of multimodal pipelines using Ollama.

Course Customization Options

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

Ollama is a platform designed to enable the local execution of large language and multimodal models while ensuring secure deployment practices.

This instructor-led, live training (available online or on-site) is targeted at intermediate-level professionals who aim to deploy Ollama with robust data privacy and regulatory compliance measures.

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

• Deploy Ollama securely in both containerized and on-premises environments.
• Apply differential privacy methods to protect sensitive information.
• Implement secure logging, monitoring, and auditing procedures.
• Ensure data access control that aligns with compliance requirements.

Format of the Course

• Interactive lectures and discussions.
• Hands-on labs focusing on secure deployment strategies.
• Case studies and practical exercises centered on compliance.

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 online or on-site) is tailored for intermediate-level finance professionals and IT personnel who aim to implement, customize, and operationalize AI solutions based on Ollama within financial environments.

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on exercises with financial data.
• Live-lab implementation of finance-focused scenarios.

Course Customization Options

• For a customized training session 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 on-site) is tailored for intermediate-level healthcare professionals and IT teams who aim to deploy, customize, and operationalize AI solutions based on Ollama within clinical and administrative settings.

After completing this training, participants will be able to:

• Install and configure Ollama for secure use in healthcare environments.
• Integrate local large language models into clinical workflows and administrative processes.
• Customize models to suit healthcare-specific terminology and tasks.
• Implement best practices for privacy, security, and regulatory compliance.

Format of the Course

• Interactive lectures and discussions.
• Hands-on demonstrations and guided exercises.
• Practical implementation in a simulated healthcare environment.

Course Customization Options

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

Ollama is a platform designed for running large language and multimodal models locally, while supporting governance and responsible AI practices.

This instructor-led, live training (available online or on-site) is targeted at intermediate to advanced professionals who aim to implement fairness, transparency, and accountability in applications powered by Ollama.

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

• Apply responsible AI principles in their Ollama deployments.
• Implement strategies for content filtering and bias mitigation.
• Design governance workflows that ensure AI alignment and auditability.
• Set up monitoring and reporting frameworks to meet compliance requirements.

Format of the Course

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

Course Customization Options

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

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

This instructor-led, live training (conducted online or on-site) is targeted at intermediate to advanced engineers who want to scale Ollama deployments in multi-user, high-throughput, and cost-efficient environments.

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

• Set up Ollama for multi-user and distributed workloads.
• Optimize the allocation of GPU and CPU resources.
• Implement strategies for autoscaling, batching, and reducing latency.
• Monitor and optimize infrastructure to enhance performance and cost efficiency.

Format of the Course

• Interactive lectures and discussions.
• Practical deployment and scaling labs.
• Real-world optimization exercises in live environments.

Course Customization Options

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

Ollama is a platform that enables the local execution of large language and multimodal models.

This instructor-led, live training (conducted online or onsite) is designed for intermediate-level practitioners who aim to master prompt engineering techniques to optimize Ollama's outputs.

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

• Create effective prompts for a variety of use cases.
• Utilize techniques such as priming and chain-of-thought structuring.
• Implement prompt templates and context management strategies.
• Develop multi-stage prompting pipelines for complex workflows.

Format of the Course

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

Course Customization Options

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