Build Local AI Models: Deploy with DeepScaler & Ollama

Discover this Free Udemy Course on local AI model deployment with DeepScaler. Start learning today!

In the age of artificial intelligence, understanding how to build and deploy AI models locally can set you apart from the crowd. “Mastering DeepScaleR” is a hands-on course designed for those eager to dive into the world of AI development without the burden of cloud-based dependencies. This course equips you with the skills needed to harness the power of open-source AI frameworks to create intelligent applications directly on your machine.

The curriculum starts by guiding you through the setup of DeepScaler and Ollama on popular operating systems like Mac, Windows, and Linux. You’ll learn to run AI models locally, enabling you to build robust applications such as AI-powered chatbots and math solvers. With a strong emphasis on fine-tuning models, you will be trained to customize DeepScaler using LoRA and QLoRA techniques to adapt the AI to specific tasks, whether it’s for enhancing financial applications, healthcare tools, or legal analysis.

You will not only develop and deploy an AI-powered math solver and chatbot but also deepen your understanding of low-latency inference and optimization techniques. By the end of this course, you will have a portfolio of locally running AI applications without incurring the high costs associated with cloud services. If you are enthusiastic about AI development and want to learn the practical skills necessary for deploying models effectively, this course is your key to success.

What you will learn:

  • Set up DeepScaler & Ollama for local AI model execution.
  • Run AI models locally without relying on cloud APIs.
  • Build an AI-powered chatbot using DeepScaler & FastAPI.
  • Develop an AI Math Solver that handles complex equations.
  • Deploy DeepScaler models via REST APIs for real-world use.
  • Integrate DeepScaler with Gradio for web-based AI tools.
  • Benchmark DeepScaler vs OpenAI models in performance tests.

Course Content:

  • Sections: 10
  • Lectures: 30
  • Duration: 8 hours

Requirements:

  • Basic Python knowledge (helpful but not mandatory).
  • Familiarity with command-line tools (Linux/Mac/Windows Terminal).
  • A computer with at least 8GB RAM (higher for better performance).
  • Ollama installed (we’ll guide you through setup).
  • Internet connection for downloading models (offline use supported after setup).
  • Interest in AI, LLMs, and model deployment.
  • No prior deep learning or ML experience needed!

Who is it for?

  • AI Developers & Engineers – Learn to build, fine-tune, and deploy AI models efficiently.
  • Data Scientists – Optimize AI-powered applications for local and enterprise use.
  • Software Developers – Integrate AI into projects without relying on cloud APIs.
  • AI Enthusiasts & Researchers – Experiment with local AI models and custom fine-tuning.
  • Tech Startups & Entrepreneurs – Deploy AI chatbots, assistants, and automation tools.
  • Students & Learners – Gain hands-on experience with AI model deployment.
  • Makers & Hobbyists – Run AI models on personal devices for fun projects.

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