8 items
AIA comprehensive guide to becoming an AI Solution Architect — from technical foundations, end-to-end AI system design skills, cloud architecture, and MLOps, to stakeholder communication soft skills. Includes role comparisons, salary benchmarks, required certifications, and common career mistakes.
Duy Tran30 min
Comprehensive study guide for the Google Cloud Professional Machine Learning Engineer exam. Vertex AI, BigQuery ML, TFX pipeline, MLOps on GCP.
An in-depth study guide for the AWS Certified Machine Learning - Specialty (MLS-C01) exam. Master SageMaker, data engineering, modeling, and ML deployment on AWS at the expert level.
A hands-on series for building a local AI stack with Gemma 4 on Apple Silicon following engineering best practices. From Ollama setup, API integration, RAG pipeline, hybrid retrieval, to observability and hardening for internal environments.
Machine Learning roadmap for beginners starts from zero, following an easy-to-understand method: intuition first, code later, just enough math. The course goes from environment setup, first model, proper evaluation, overfitting/data leakage prevention, to common models (Linear, Logistic, Tree, XGBoost), unsupervised, time series, and production deployment. Each cluster of lessons has mini-projects, real-life challenges and a clear output checklist.
In-depth series on Enterprise AI Chatbot Platform system architecture: multi-model gateway, RAG pipeline, agentic architecture (multi-agent orchestration, tool calling, planning & reflection), conversation memory, streaming & voice, guardrails & safety, multi-channel deployment, multi-tenant architecture, analytics & observability, evaluation & optimization, GPU infrastructure & model serving. Build an enterprise-level chatbot platform from A-Z, ready for production.
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.
In-depth course on MLOps and LLMOps — the art of bringing AI models from prototype to production safely and effectively. From experiment tracking, CI/CD for ML, to LLM observability, cost optimization, guardrails, and compliance. Highest paying skills in AI.