[UDM] Open-source LLMs: Uncensored & secure AI locally with RAG Course (Feb 2025) + Resources

Run LLMs Locally Without Coding
The Open-source LLMs: Uncensored & secure AI locally with RAG Course will be the key to the mastery of the world of open-source large language models (LLMs) and running them with your hardware entirely. Bye-bye platform walls and welcome freedom to move with complete control, privacy, and flexibility. You will venture into the advantages of working with such models as Llama 3, Mistral, Phi-3, Grok, and Gemma, of course, knowing how they compare to commercial models such as ChatGPT. Focusing on privacy, performance, and no censorship, this course would provide you with the basis to build your own personal AI assistant that would not be controlled by others.

Local Run LLMs Locally LLMs Without Coding
Although you, as a non-programmer, will not learn to write ready-made AI programs, you will be equipped with the information necessary to deploy an AI model on a local device with the help of simple tools such as LM Studio, Anything LLM, and Ollama. The Open-source LLMs: Uncensored & secure AI locally with RAG Course takes you through the process of installing such systems, choosing the proper models, and tuning the performance depending on your hardware, i.e., CPU, GPU, or even a custom LPU such as Groq. You will also practice parameterizing models on these platforms as Hugging Face or Google Colab, and look into vision-enabled LLMs such as Llava and Phi-3 Vision.

Build Smart AI Apps with RAG and Prompt Engineering
You’ll dive deep into prompt engineering techniques and system prompt design to get the most accurate and useful responses from your models. Then, you’ll build your own Retrieval-Augmented Generation (RAG) chatbot that can answer real-time questions using your documents and data. Tools like Anything LLM, LM Studio, and vector databases make this process easy and powerful. You’ll also explore function calling with Llama 3 to trigger tasks like summarizing content, generating charts, and even writing code—all done securely on your device.

Go Beyond Chatbots: AI Agents, Automation & Safety
The Open-source LLMs: Uncensored & secure AI locally with RAG Course doesn’t stop at chatbots. You’ll also build AI agents using platforms like Flowise, LangChain, and LangGraph that can interact with web data, generate code, or even manage tasks across different tools. You’ll learn how to optimize these systems using services like Firecrawl and LlamaIndex, and how to run models in the cloud using services like RunPod if your local hardware isn’t enough. On top of that, you’ll gain a clear understanding of potential security threats such as prompt injection and data poisoning, along with best practices to keep your AI systems safe and reliable.