How to Learn Local AI App Development Free
Download and stream DeepSeek R1 & Ollama premium course free to master local AI tools, deploy models, and build powerful applications.
DeepSeek R1 & Ollama Guide Overview:
This premium video course is completely free and teaches you how to build local AI applications using DeepSeek R1 and Ollama. You’ll gain full control, privacy, and cost efficiency while deploying large language models. The course helps you select the right model variants like 1.5B or 7B based on your hardware capabilities and specific needs. Whether you’re developing chat interfaces or AI assistants, this training prepares you to work independently with modern AI tools and frameworks.
Instructor Paulo Dichone, an expert in cloud and mobile development, guides you through every concept using Python to build real-world applications. You will explore performance optimization and production-grade deployment strategies to scale your AI projects. With this free resource, you’ll learn to implement AI features into mobile and cloud environments, pushing your development skills into the future.
Learn to build, deploy, and scale AI applications locally—fully free.
What You’ll Learn in DeepSeek R1 & Ollama Guide:
- Deploy DeepSeek R1 locally using Ollama for full control
- Select and configure model variants based on your setup
- Develop Python-based apps: chatbots, assistants, and tools
- Optimize performance for real-world production use
- Integrate AI into mobile apps and cloud systems
Course Highlights:
- Hands-on Projects: Build AI tools from scratch using real examples
- Model Training: Work with different model sizes (1.5B, 7B, full)
- Python Focus: Use Python for all AI integrations and tools
- Real-World Use: Apply skills in actual software environments
- Cloud Integration: Extend AI apps into AWS cloud services
DeepSeek R1 & Ollama Info:
This free video course, created by Paulo Dichone and published on Udemy, focuses on using DeepSeek R1 and Ollama to build local AI applications. It emphasizes hands-on experience with LLM deployment, performance optimization, and AI tool creation. Released in February 2025, the course uses Python and targets developers who want privacy-focused, scalable AI implementations without relying on external APIs. With 914 MB of course files and instruction in English, it’s ideal for developers aiming to modernize their workflow using local AI solutions.
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