AI Solutions Architecture and System Design

As organizations rapidly integrate artificial intelligence into their operations, the need for structured system design has never been greater. This course bridges the gap between basic AI usage and professional architecture, teaching you how to build scalable and reliable AI solutions. You will gain the skills to evaluate different model types, design efficient data pipelines, and architect systems that solve complex problems using modern frameworks. What you'll learn: - Understand the fundamental components and layers of a modern AI architecture - Master prompt engineering techniques to optimize model output and reliability - Implement Retrieval-Augmented Generation (RAG) patterns to connect models to private data - Evaluate and select appropriate Large Language Models (LLMs) for specific business needs - Configure vector databases for efficient high-dimensional data retrieval - Apply AI governance and security best practices to protect system integrity The course begins with essential terminology and core concepts before moving into practical design patterns and integration strategies. Through written explanations and technical examples, you will explore how to transition from simple AI experiments to production-ready system architectures. This program is designed for beginners, technical leads, and aspiring architects who want to understand the structural side of AI without requiring a deep background in data science. Start your journey toward becoming a proficient AI solutions architect today.