This repository compiles over 100 interview questions for Large Language Models (LLMs), targeting candidates for roles at major tech companies like Google, NVIDIA, Meta, and Microsoft. It aims to provide a structured learning resource for individuals preparing for LLM-focused interviews, covering a broad spectrum of topics from foundational concepts to advanced deployment strategies.

How It Works

The repository organizes LLM interview questions into 15 distinct categories, including Prompt Engineering, Retrieval Augmented Generation (RAG), Embedding Models, Vector Databases, and LLM Fine-Tuning. This categorization facilitates targeted preparation by allowing users to focus on specific areas of LLM technology. The questions are curated to reflect real-world scenarios and common interview topics encountered in top tech companies.

Quick Start & Requirements

• Access: No installation required; questions are directly available in the README.
• Resources: Answers and further explanations are available via the "Mastering LLM" platform, with a potential discount code "LLM50" mentioned.

Highlighted Details

• Comprehensive coverage of 15 key LLM domains.
• Questions sourced from interviews at leading technology firms.
• Includes practical aspects like cost estimation and deployment optimization.
• Features case studies for applied learning.

Maintenance & Community

• The repository appears to be a static collection of questions.
• Further learning resources are directed to an external platform, "Mastering LLM."

Licensing & Compatibility

• The repository itself does not specify a license.
• Content is for educational and preparation purposes.

Limitations & Caveats

The repository provides questions but not answers directly within the repository; external resources are required for explanations. The mention of a discount code suggests a commercial aspect to the learning resources.