Ollama LLM Essentials is a foundational training program designed to introduce participants to locally hosted large language models using Ollama. This course focuses on understanding how Ollama works, running LLMs locally, interacting with models effectively, and applying Ollama for real-world use cases while maintaining data privacy and control. The training emphasizes practical usage without reliance on cloud-based or paid AI tools.

• Understand Ollama and LLM fundamentals
• Set up and manage local language models
• Run and interact with Ollama-based AI models
• Apply prompt engineering basics for LLMs
• Use Ollama for practical AI applications

• Developers and engineers
• IT and infrastructure professionals
• AI enthusiasts and beginners
• Data privacy-focused organizations
• Students and technical professionals

• Basic computer and system usage skills
• Familiarity with command-line or desktop applications
• No prior AI, machine learning, or programming experience required

• Understanding local LLM concepts and Ollama architecture
• Running and managing LLMs locally using Ollama
• Interacting with LLMs effectively through prompts
• Selecting appropriate models for different tasks
• Applying privacy-first AI practices

By the end of this training, participants will be able to confidently run and use Ollama for local LLM applications. Learners will gain practical knowledge to select models, design prompts, and apply Ollama responsibly for everyday AI use cases.

Introduction to Local LLMs and Ollama
• Overview of large language models
• Local vs cloud-based LLMs
• Use cases and benefits of Ollama

Getting Started with Ollama
• Installing and setting up Ollama
• Running and managing models
• Understanding system requirements and performance

Understanding Ollama Models
• Model types and sizes
• Choosing the right model for tasks
• Managing model versions and updates

Interacting with LLMs Using Ollama
• Basic prompting techniques
• Managing input and output length
• Understanding response behavior

Prompting Basics and Best Practices
• Writing clear and effective prompts
• Structuring instructions and context
• Avoiding common prompting mistakes

Practical Use Cases with Ollama
• Content generation and summarization
• Coding and technical assistance
• Research and knowledge support

Performance, Limitations, and Troubleshooting
• Understanding latency and resource usage
• Handling errors and unexpected outputs
• Model limitations and trade-offs

Security, Privacy, and Responsible AI Usage
• Data privacy advantages of local LLMs
• Ethical considerations
• Responsible deployment practices

Hands-on Ollama Practice Sessions
• Real-world usage scenarios
• Guided exercises and experimentation
• Participant practice and feedback

• Introduction to LLMs and Ollama
• Ollama installation and configuration
• Prompting and model interaction
• Local AI workflow development
• Model performance and optimization

• Participation in hands-on exercises
• Prompt-based practical assignments
• Scenario-driven assessment

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training and evaluation will receive an AcadNXT Certificate of Completion in Ollama LLM Essentials, validating their foundational skills in using Ollama for local LLM deployments.