1. What is Data Science?
  2. What is logistic regression in Data Science?
  3. Name three types of biases that can occur during sampling
  4. Discuss Decision Tree algorithm
  5. What is Prior probability and likelihood?
  6. Explain Recommender Systems?
  7. Name three disadvantages of using a linear model
  8. Why do you need to perform resampling?
  9. List out the libraries in Python used for Data Analysis and Scientific Computations.
  10. What is Power Analysis?
  11. Explain Collaborative filtering
  12. What is bias?
  13. Discuss 'Naive' in a Naive Bayes algorithm?
  14. What is a Linear Regression?
  15. State the difference between the expected value and mean value
  16. What the aim of conducting A/B Testing?
  17. What is Ensemble Learning?
  18. Explain Eigenvalue and Eigenvector

TOP MNC DATA SCIENCE INTERVIEW QUESTIONS