This interview preparation course is designed to help aspiring AI engineers, machine learning developers, and generative AI professionals prepare for technical interviews focused on large language models (LLMs) and modern AI systems. The course covers the most common and important interview questions asked in AI and LLM-related roles.

You will begin by reviewing the foundations of large language models, including transformers, tokenization, embeddings, attention mechanisms, and generative AI workflows. These concepts are frequently discussed in technical interviews for AI engineering positions.

The course also explores practical LLM topics such as prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), vector databases, and inference optimization. Each question is explained in a simplified way to help learners understand both the theory and practical applications behind modern AI systems.

You will also learn how to answer scenario-based and conceptual interview questions related to AI agents, model training, scalability, and production deployment. This helps improve confidence during technical discussions and coding interviews.

By the end of this course, you will have a stronger understanding of key LLM concepts and be better prepared for AI job interviews in machine learning, NLP, and generative AI fields.

This course is ideal for students, developers, and professionals preparing for careers in AI and large language model engineering.