Most AI development relies on expensive cloud APIs like OpenAI, which cost money per request and send your data to third parties. This course teaches you how to build, fine tune, and deploy AI models locally using DeepScaleR (a fine tuned version of DeepSeek R1 Distilled Qwen 1.5B) and Ollama. You will set up local AI models, build an AI powered chatbot, develop an AI math solver for complex equations, deploy models via REST APIs with FastAPI, fine tune DeepScaleR using LoRA and QLoRA on custom datasets, create a code assistant, and benchmark DeepScaleR against OpenAI models.

This Course Offers

• Complete setup of DeepScaleR and Ollama on Mac, Windows (WSL), or Linux.
• Local AI model execution without cloud API costs or privacy concerns.
• FastAPI deployment for AI powered chatbots and math solvers.
• Fine tuning with LoRA and QLoRA for domain specific tasks (finance, healthcare, legal).
• AI code assistant for generation, debugging, and code explanation.
• Gradio for interactive AI powered web applications.

Why We Love This Course

1. It focuses on local, private, cost free AI. No recurring API bills.
2. Over 20,000 students have enrolled, and the course is hands on from the first lecture.
3. DeepScaleR is optimized for math reasoning, code generation, and AI automation, making it highly practical.
4. The instructor covers both deployment and fine tuning, so you can adapt models to your own data.

A note from student feedback: some noted that the description mentions LoRA and QLoRA fine tuning, but the course may not cover it in depth. Check the curriculum before enrolling. However, for building and deploying local AI chatbots, math solvers, and code assistants with DeepScaleR and Ollama, this course provides a solid, practical foundation.

• AI developers and engineers who want to build, fine tune, and deploy AI models efficiently.
• Data scientists optimizing AI powered applications for local and enterprise use.
• Software developers integrating AI into projects without cloud APIs.
• AI enthusiasts and researchers experimenting with local AI models and custom fine tuning.
• Tech startups and entrepreneurs deploying AI chatbots, assistants, and automation tools.
• Students and learners gaining hands on experience with AI model deployment.
• Makers and hobbyists running AI models on personal devices for fun projects.
• Privacy conscious users who do not want to send their data to OpenAI or other cloud providers.

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

Interested in exploring more lessons? Check out our full course library to continue building your skills and advancing your learning journey.