# GenAI & LangChain (Data Science & ML)

> LLMs (GPT, Gemini, Claude), prompting, LangChain, chains, agents, RAG, vector stores, embeddings

- 24 interview questions
- Senior
- [Interview Questions: Data Science & ML](https://sharpskill.dev/en/technologies/data-science/interview-questions.md)

## 1. What is an LLM (Large Language Model)?

**Answer**

An LLM is a deep learning model trained on massive amounts of text to understand and generate natural language. These models use the Transformer architecture with billions of parameters, enabling them to capture language nuances, follow complex instructions and generate coherent text. GPT-4, Claude and Gemini are examples of LLMs used in production.

## 2. What is the main difference between zero-shot and few-shot prompting?

**Answer**

Zero-shot prompting asks the model to perform a task without providing prior examples, relying only on instructions. Few-shot prompting includes a few input/output pair examples in the prompt to guide the model. Few-shot generally improves performance on specific tasks because the model can infer the expected format and style from the provided examples.

## 3. What is chain-of-thought (CoT) prompting?

**Answer**

Chain-of-thought prompting is a technique that encourages the LLM to break down its reasoning step by step before giving its final answer. By adding phrases like 'Let's think step by step' or showing reasoning examples, performance on logical, mathematical or multi-step reasoning tasks improves significantly. This approach also makes the decision process more transparent and verifiable.

## 21 more questions available

- What is LangChain and what is its main objective?
- What is a chain in LangChain?

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