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Suppose you are preparing for a job in data science, machine learning engineer, artificial intelligence engineer, or research scientist. In that case, you should look for excellent resources to help you succeed in your interview.
Deep learning is becoming increasingly popular, as it forms the basis of topics such as large language models and generative ai, as well as combining many different concepts. That's why this interview prep course is probably one of the best things I've seen in a long time.
Not only will you gain a great basic and experienced knowledge of deep learning, but you will also improve your skills in data science and machine learning. Even if you are not preparing for any interviews but are on a learning journey, I would recommend this interview prep course!
This course consists of 2 parts. In the first part, the video will review the top 50 questions with their corresponding answers. In the second part, the video will review the remaining 50 questions.
100 questions in total. That's 7.5 hours total!
Basic interview questions
You will start with the basics of deep learning, neural network concepts, neural network architecture, activation functions, and gradient descent. These are the first 10 questions, so you'll get through them pretty quickly.
Intermediate Interview Questions
In the next 20 questions, you'll dig a little deeper and be able to define how backpropagation is different from gradient descent and cross entropy. From there, you'll delve a little deeper and test your skills in areas like Stochastic Gradient Descent and Hessian and how they can be used to speed up the training process.
Expert interview questions
The last 20 questions will test your knowledge with topics such as Adam and its use in neural networks, what is layer normalization, residual connections and how to solve exploding gradients. You'll also learn more about dropout and what it is, how it prevents overfitting, the curse of dimensionality, and more.
We hope this course has helped you become more confident for your next interview or your learning process in general. Reviewing the top interview questions will help you understand what important knowledge is and what interviewers consider important skills and knowledge.
If you know of other good resources, please share them in the community comments!
nisha arya is a data scientist, freelance technical writer, and KDnuggets editor and community manager. She is particularly interested in providing professional data science advice or tutorials and theory-based insights into data science. Nisha covers a wide range of topics and wants to explore the different ways in which artificial intelligence can benefit the longevity of human life. Nisha, a great student, seeks to expand her technological knowledge and her writing skills, while she helps mentor others.
