Foundational AI Engineering for LLM Interviews

Are you looking to break into AI engineering or strengthen your understanding of large language models (LLMs) for technical interviews? This course will equip you with the essential knowledge and practical understanding required to discuss core AI engineering principles and modern LLM architectures with confidence. You will learn the fundamental theory and practical considerations behind building and deploying AI systems. What you'll learn: * Learn foundational machine learning concepts relevant to AI engineering * Understand the architecture and mechanics of transformer models for LLMs * Explore the lifecycle of training, fine-tuning, and evaluating large language models * Apply principles of efficient model inference and deployment strategies * Grasp modern prompt engineering techniques and basic retrieval-augmented generation (RAG) patterns * Develop an understanding of MLOps principles for productionizing AI systems The course begins with core machine learning principles, then progresses through the intricacies of transformer architectures and LLM lifecycle stages, concluding with practical considerations for inference, deployment, and modern LLM application patterns. This course is designed for beginners with an interest in AI engineering and large language models, requiring no prior specialized knowledge in the field. Start building your AI engineering expertise today.