Acad ID: ACAD0310

Ollama LLM Essentials Training in New York City, United States

This course focuses on understanding how Ollama works, running LLMs locally, interacting with models effectively, and applying Ollama for real-world use cases.

Overview

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.

Learning Outcomes

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

Duration & Delivery Mode

14 hours

We serve:

Target Audience

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

Pre-requisites

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

Skillset Achieved

• 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

Course Outcome

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.

Course Outline

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

Assessment Topics

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

Evaluation

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

Course Materials

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

Certification

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.

SELECT AN UPCOMING CLASS

Fri 23rd Oct 2026 – Sat 24th Oct 2026

⏱ 2 days 📍 Classroom