[73% Off] Master Llm And Gen Ai: 600+ Real Interview Questions[2025]

600+ Questions: Transformer Architecture, Self-Attention,Positional Encoding, Real Questions asked by Leading Tech Firms

Added on August 16, 2025 IT & Software 4 min read

What you’ll learn

This course serves as a thorough preparation tool for individuals gearing up for job interviews that demand LLM(Large Language Model) programming skills.
The course encompasses a diverse range of questions
addressing various facets of LLM(Large Language Model) programming like Transformer
Attention
Embeddings
Each question in the course is meticulously crafted to evaluate your LLM(Large Language Model) programming expertise and problem-solving abilities.
This course is designed not only to help you succeed in interviews but also to improve your overall LLM(Large Language Model) programming expertise.
Do the questions have explanations? Yes

Requirements

Basic understanding of Machine Learning and Data Science

Description

This course features 600 Real and Most Asked Interview Questions that leading tech companies have asked. Unlock the secrets of Large Language Models (LLMs) and Generative AI with our expertly designed course, “LLM & GenAI Interview Questions and Answers: Basic to Expert” This is your ultimate guide to mastering the concepts, techniques, and challenges of modern AI systems, helping you stand out in interviews and advance your career in AI and machine learning.

Are you ready to dominate your next interview in the exciting world of Large Language Models (LLMs) and Generative AI? Look no further! This course is your ultimate guide to mastering LLMs and cracking interviews, whether you’re a beginner or an aspiring expert.

This course takes you on a journey from foundational knowledge to advanced concepts, covering key topics such as prompt engineering, model fine-tuning, transformer architecture, ethical AI considerations, and real-world applications. Whether you’re preparing for technical interviews or just want to deepen your understanding of cutting-edge AI technologies, this course has you covered.

Our interactive format includes real interview questions asked by leading tech companies, along with detailed answers and explanations to build your confidence. Through hands-on exercises and scenario-based problem-solving, you’ll develop practical skills that are directly applicable to industry demands.

Designed for aspiring data scientists, software engineers, and AI enthusiasts, this course is a must-have resource to sharpen your expertise and stay ahead in the rapidly evolving AI landscape. Enroll now and take the first step toward becoming an AI expert ready to tackle any interview challenge!

Why Enroll in This Course?

Imagine walking into an interview with full confidence, armed with in-depth knowledge and hands-on practice. In this course, you’ll:

Master key concepts from Transformer Architecture to Tokenization.

Dive deep into advanced topics like Multi-Head Attention, Residual Connections, and Mixed-Precision Training.

Learn by solving basic to expert-level interview questions, ensuring you’re fully prepared for real-world challenges.

What Will You Learn?

Here’s just a sneak peek at what’s waiting for you:

1️. Transformer Architecture – The backbone of LLMs.

2️. Attention Mechanism – Powering breakthroughs in AI.

3️. Positional Encoding – Understanding how sequences matter.

4️. Tokenization – Decoding text like a pro.

…and so much more!

Sample Questions:

1. You need to deploy a fine-tuned large language model on a device with limited memory. The full model size exceeds the device’s capacity. What strategy would you use to make deployment feasible?

A) Prune the model by removing entire layers.

B) Compress the model by quantizing all parameters.

C) Fine-tune using PEFT and deploy only the adapted parameters alongside the pre-trained model.

D) Reduce the vocabulary size used by the model.

2. During the fine-tuning of a large model, you observe that the gradients of most parameters are close to zero, resulting in slow convergence. How would you address this issue?

A) Increase the number of epochs to allow for better convergence.

B) Apply LoRA to focus the adaptation on low-rank components.

C) Implement gradient clipping to control large updates.

D) Use a larger learning rate to accelerate convergence.

By the End of This Course:

You’ll confidently tackle advanced LLM concepts like Perplexity and Mixed-Precision Training and understand cutting-edge AI techniques that top companies are looking for.

Who Should Join?

If you have a basic understanding of Machine Learning, this course will take you to the next level. Whether you’re a student, a job seeker, or a professional looking to upskill, this course is for YOU.

Take Action Now!

Don’t miss this chance to supercharge your career in AI. Join me on this exciting journey to master LLMs and Generative AI! Enroll now in the “LLM and Gen AI Interview Questions: Basic to Expert” course on Udemy.

Your future in AI starts today! Click “Enroll Now” and take the first step toward your success!

Enroll today and equip yourself with the knowledge and practice needed to succeed in the world of Large Language Models (LLMs) Programming by mastering real questions that leading tech companies have asked.