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I applied via Naukri.com and was interviewed in Feb 2024. There were 2 interview rounds.
Excel, Python, SQL and Power BI
Remove duplicates from an array without using any functions
Create an empty array to store unique values
Loop through the original array and check if the value is already in the unique array before adding it
Use nested loops to compare each element with all other elements in the array
To create a single dimensional array from a multi dimensional array, use the flatten method in Python.
Use the flatten method in Python to convert a multi dimensional array into a single dimensional array.
Example: multi_array = [[1, 2], [3, 4], [5, 6]]
single_array = [item for sublist in multi_array for item in sublist]
It was based upon Tableau
Top trending discussions
I applied via Campus Placement
Good very good have a nice day
I applied via Naukri.com and was interviewed in Sep 2024. There were 2 interview rounds.
Easy to moderate general aptitude questions were asked
Easy to moderate questions were asked
It is the 30 mins of mathatic question and easy done .
2 QUESTIONS are give ,you have to solve the q in 30 mins
I applied via Campus Placement
Assignment was based on figma
I applied via Monster and was interviewed before Apr 2023. There were 3 interview rounds.
Question are hard in panel
I am currently earning a salary of $60,000 per year.
My current annual salary is $60,000
I am earning $5,000 per month
My total compensation package is $60,000
The company name is XYZ Corporation, a leading data analytics firm specializing in providing insights for businesses.
XYZ Corporation is a data analytics firm
Specializes in providing insights for businesses
It is very good in study for
Further studies.
I applied via campus placement at Indian Institute of Technology (IIT), Bhuvaneshwar and was interviewed before Oct 2023. There were 2 interview rounds.
Basic aptitude tests 50 questions for 1 hr
1) find number of set bits in given number
2) add to numbers represented by linked list
I applied via Naukri.com and was interviewed in Dec 2021. There were 3 interview rounds.
Assumptions of linear regression model
Linearity: relationship between independent and dependent variables is linear
Independence: residuals are independent of each other
Homoscedasticity: variance of residuals is constant across all levels of predictor variable
Normality: residuals are normally distributed
No multicollinearity: independent variables are not highly correlated with each other
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