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Comprehensive guide to running LLM locally on Mac Apple Silicon (M1/M2/M3/M4) with Ollama and MLX. From initial installation to 3x acceleration with the MLX framework, managing multiple models, integrating APIs into applications, and optimizing GPU/RAM performance. All hands-on, privacy-first, no internet required.
The series builds an entire AI system for a Fashion & Print-on-Demand platform — from AI Design Generation (Stable Diffusion, ControlNet), AI Editing in natural language, Personalization System, Virtual Try-On with Computer Vision, to Print File Optimization and AI Product Generation. Each article is an independent AI module that can be deployed in production.
A hands-on series on building a complete AI Agent Platform using TypeScript — from monorepo design, LLM Router, Tool Registry, RAG Pipeline, Workflow Engine, Multi-tenant RBAC to deploying Docker production. Learn through the actual source code of xClaw — an open-source platform running in production.
Practical course on Computer Vision — from CNN, Object Detection (YOLO), Image Segmentation (SAM) to Vision Transformer and Multimodal AI. Hands-on with PyTorch, Ultralytics YOLO, Hugging Face. Deploy CV model to production with TensorRT and ONNX.
Comprehensive course on Prompt Engineering — from writing basic prompts to Chain-of-Thoughts, Tree-of-Thoughts, Multimodal Prompting and building a Prompt Library for production. The most essential skill in the AI age, immediately applicable to ChatGPT, Claude, Gemini.
In-depth course on Retrieval-Augmented Generation (RAG) — techniques for connecting the LLM to your own data. From basic RAG to Graph RAG, Agentic RAG, Multimodal RAG. Hands-on with ChromaDB, Qdrant, LangChain, LlamaIndex. Deploy "Chat with Documents" to production.
Comprehensive course on Fine-tuning Large Language Models — when to fine-tune, data preparation, fine-tuning on Google Gemini/Vertex AI, OpenAI, and open-source (LoRA/QLoRA). Compare Fine-tuning vs RAG, model evaluation methods, and production deployment. Calculate actual costs.
Practical course on building AI Agents — from simple chatbots to complex Multi-Agent systems. Proficient in Function Calling, Tool Use, RAG, MCP, LangGraph, CrewAI and deploying Agent to production. Each lesson is coded hands-on with Python.
Comprehensive course on Artificial Intelligence and Large Language Models — from Neural Networks platform, Transformer architecture, to Fine-tuning, RAG, AI Agents and production deployment. Learn hands-on with Python, PyTorch, and LLM APIs.
Comprehensive basic to advanced Kubernetes course for 2026, helping you master container orchestration, deploy production-ready applications, and prepare for CKA/CKAD certification. Updated to Kubernetes 1.32+ with Gateway API, Cilium, OpenTelemetry, Helm 4, Sidecar containers GA, ValidatingAdmissionPolicy, and AI/ML workloads.