Top universities of the world says that data science is the most demanding job in this century. Even some of the top online job portals saw a huge surge in data science jobs in the last 2 years.

Some top MNC’s found that there will be 50% more recruitment in data science in upcoming years. As the internet getting cheaper day by day, there is an explosion in data. with cheaper internet, every small to large business uses the internet for their growth.

The use of the internet generates data on both the consumer and seller sides. It is quite evident that the use of the internet is directly proportional to the amount of data generated or recorded.

Top MNC’s uses this data to unearth hidden information that directly or indirectly helps business to grow. This ecosystem has made data science the most lucrative job of this century.

In this blog, we shall list out top data science interview questions that can help you to crack the interviews of top MNC’s.

Data science interview Questions:

1. What is the difference between supervised and unsupervised learning?
2. Give some examples of supervised and unsupervised learning?
3. What is a machine learning model?
4. What is logistic regression?
5. what is the difference between linear regression and linear classification?
6. What are homoscedasticity and heteroscedasticity?
7. What is the difference between R square and adjusted R squared?
8. What different steps for data preprocessing?
9. What is an outlier? How to detect and remove outliers?
10. Why scaling of features is required?
11. What is P-value?
12. What is ANOVA and how it helps to select features?
13. What is the difference between one-way and two-way ANOVA?
14. What is colinearity?
15. What is VIF?
16. What is the 5 point summary?
17. How can we visualize 5 point summary?
18. What is skewness?
19. What is a central mean theorem?
20. What is the correlation? how it can be used to select features?
21. How to find a correlation to categorical features?
22. What is a decision tree?
23. What is a random forest?
24. What is bagging and boosting?
25. What is ensemble methods?
26. What are the different techniques that are used to split a node in the random forest?
27. Which technique is used to split a node for a random forest regressor?
28. How to check overfitting in the random forest?
29. What are the hyperparameters of the random forest?
30. What is the different error measuring method?
31. What is a confusion matrix?
32. What is the f1 score? and when we should consider it?
33. What is sensitivity, specificity, precision, recall, accuracy?
34. What is the AOC RUC curve?
35. What is an imbalanced dataset?
36. How to deal with an imbalanced dataset?
37. What is the support vector machine?
38. What is the decision boundary?
39. What is a hyperplane?
40. What is the bias-variance tradeoff?
41. What are kernels in SVM?
42. What is a neural network?
43. What is activation functions?
44. Why activation functions are used?
45. Why GPU is preferred for building a neural network?
46. What is gradient ascent/descent?
47. Which activation function can be used for the multiclass neural network?
48. What are the weights in neural networks?
49. What the different weight initialization techniques in neural networks?
50. What is backpropagation?
51. what is r-square and adjusted r-squared?
52. what are ensemble methods?
53. explain exploding and vanishing gradient?
54. what are eigenvalue and eigen vector?
55. what is central mean theorem?
56.  what is recursive feature elimination?
57. what are kernels in svm?

 

Conclusion:

In this blog, we listed the top 55 data science interview questions. The above questions are the most frequently asked question of any data science interview in 2021. We shall keep on updating this list. Hope this list help will help to crack the interview.