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 Duration 7 hours

Course Outline

Ollama Fundamentals

  • Defining Ollama and its operational mechanics
  • Advantages of local AI model execution
  • Summary of compatible LLMs (including Llama, DeepSeek, and Mistral)

Ollama Installation and Configuration

  • Hardware specifications and system prerequisites
  • Installing Ollama across various operating systems
  • Setting up necessary dependencies and environment variables

Executing AI Models Locally

  • Acquiring and loading AI models within Ollama
  • Communicating with models through the command line
  • Basic prompt engineering techniques for local AI

Performance Optimization and Resource Management

  • Handling hardware resources for optimal AI performance
  • Minimizing latency and enhancing response speeds
  • Conducting performance benchmarks across different models

Applications for Local AI Deployment

  • Building AI-driven chatbots and virtual assistants
  • Automating data processing workflows
  • Developing privacy-centric AI solutions

Recap and Future Directions

Requirements

  • Foundational knowledge of AI and machine learning principles
  • Proficiency with command-line tools

Target Audience

  • Developers seeking to run AI models independent of cloud services
  • Business leaders prioritizing AI privacy and cost-efficient deployment
  • AI hobbyists interested in local model management

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