Prompt Engineering Mastery with Ollama Training Course

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.

This instructor-led, live training session in Malaysia (online or onsite) is designed for beginner-level professionals eager to install, configure, and utilise Ollama to run AI models on their own devices.

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

• Grasp the fundamentals of Ollama and its key capabilities.
• Configure Ollama to run local AI models.
• Deploy and interact with LLMs using Ollama.
• Optimise performance and resource allocation for AI workloads.
• Explore practical applications for local AI deployment across various industries.

This live, instructor-led training in Malaysia empowers finance practitioners and IT staff with the competencies to implement Ollama locally. Learners will focus on deploying, configuring, and integrating large language models into secure financial workflows, while adhering to best practices for regulatory compliance and automation.

This live training in Malaysia enables healthcare professionals and IT teams to implement Ollama for local LLM deployment. Gain insights into integrating AI into clinical workflows, tailoring models for specific duties, and upholding rigorous data privacy and regulatory standards within secure healthcare ecosystems.

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