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Nvidia Interview Experience for QA SDET Intern (On-Campus)

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Interview process held in Nov 2021 for internship duration of 5 months starting from Jan to Jun. Hackerrank test consists of 2 coding problems, OS, computer fundamental, and logical reasoning.

Shortlisted about 16-20 students. The interview duration was 1 Hr. there were two interviewers on MS Teams. One was asking CPP questions and the other was asking python 

  • Questions were based on Project
  • What is the difference between lemming vs stemming
  • What are things from NLP you used?
  • Do you know any text classification algorithms?
  • Define a string of length l in python
  • Tell me about dynamic memory allocation
  • What is the difference between LIFO vs FIFO
  • Create a new list of words from the given list where the substring ‘ant’ is present in the word
  • Asked me to code for max min element from the array
  • There were a question  about hardware 
  • What is the difference between SSD and HDD?
  • Types of SSD?
  • Tell me CPU parts.
  • How computer boots, bios?
  • What is blod, and how did it has occurred?
  • Which games you played did yed what game settings you change (FPS, resolution)
  • How to disable/enable storage devices from bios?
  • How to block any service or app at startup
  • They asked quean stion on ML also as there was opening for ML tool developer.
  • Working and equation of SVM regressor ?
  • Situation-based q on ML algorithm to choose.
  • What is convolution ?
  • Difference between logistic and linear regression
  • Whado t is neural network
  • Which graphics card you know which is latest GPU
  • Hopefully I was able to answer the moan and st of the questions and I got the offer for internship.
  • IMP topics to study
    • Davisualizationion and data cleaning
    • Different types of ML models and how they work
      For Eg: regression and types of regression and how they work (algorithm)
    • If you have studied DNNs then
      Back and forward propagation, model training, neurons, and DNN layers, gradient descent algorithm, cost optimization
      These are just the basic things expected to have
    • Then you have your model analysis part
      Errors (rmse, r-squared, least squares, etc)
      Then there is model metrics (accuracy, precision, etc)
      This much if you can cover it would cover most the things that can be asked
Last Updated : 28 Jul, 2022
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