Kyndryl Senior Data Scientist Interview Questions, Process, and Tips

Extract India players from a dictionary using list comprehension

• Use list comprehension to filter out players with nationality as 'India'

• Create a new list with only the India players

• Example: [player for player, nationality in CSK.items() if nationality == 'India']

Use sets to find common elements in three lists.

• Convert the lists to sets for efficient comparison.

• Use the intersection method to find common elements.

• Return the common elements as a set or list.

Printing specific rows from a database using Pandas in Python

• Use Pandas library to read the database into a DataFrame

• Use iloc method to select specific rows by index

• Print the selected rows

Use scikit-learn library to split dataset into train, test, and validation sets

• Import train_test_split from sklearn.model_selection

• Specify test_size and validation_size when splitting the dataset

• Example: X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

Use DISTINCT keyword to print unique values and DELETE with a subquery to remove duplicate rows.

• Use SELECT DISTINCT column_name FROM table_name to print unique values.

• Use DELETE FROM table_name WHERE row_id NOT IN (SELECT MAX(row_id) FROM table_name GROUP BY column_name) to delete duplicate rows.

Use SQL SELECT statement with WHERE clause to filter rows based on a specific criterion.

• Use SELECT statement with WHERE clause to specify the criterion (ex: salary > 100000)

• Example: SELECT * FROM employees WHERE salary > 100000;

• Ensure proper syntax and column names are used in the query

Use subquery to find rows with second highest criterion value in SQL without using offset function.

• Use a subquery to find the maximum criterion value

• Then use another subquery to find the maximum value that is less than the maximum value found in the first subquery

• Finally, select rows with the second highest criterion value

Print rows with the same set of values in a column

• Identify unique sets of values in the column

• Group rows based on these unique sets of values

• Print out the rows for each unique set of values

Power BI is a Microsoft product focused on business intelligence and data visualization, while Tableau is a standalone data visualization tool.

• Power BI is more user-friendly and integrates well with other Microsoft products.

• Tableau is known for its powerful data visualization capabilities and flexibility in creating complex visualizations.

• Power BI is often preferred by organizations already using Microsoft products, wh...read more

Power BI and Tableau have limitations in terms of data connectivity, customization, and pricing.

• Limited data connectivity options compared to other tools

• Limited customization capabilities for advanced analytics

• High pricing for enterprise-level features

• Tableau has better visualization capabilities but can be more complex to use

• Power BI is more user-friendly but may lack certain advanced features

Types of regression models include linear regression, logistic regression, polynomial regression, ridge regression, and lasso regression.

• Linear regression: used to model the relationship between a dependent variable and one or more independent variables.

• Logistic regression: used for binary classification problems, where the output is a probability value between 0 and 1.

• Polynomial regression: fits a curve to the data by...read more

Linear regression is used for continuous variables, while logistic regression is used for binary outcomes.

• Linear regression predicts continuous outcomes, while logistic regression predicts binary outcomes.

• Linear regression uses a linear equation to model the relationship between the independent and dependent variables.

• Logistic regression uses the logistic function to model the probability of a binary outcome.

• Linear reg...read more

Random Forest is an ensemble method using multiple decision trees, while Decision Tree is a single tree-based model.

• Random Forest is a collection of decision trees that are trained on random subsets of the data.

• Decision Tree is a single tree structure that makes decisions by splitting the data based on features.

• Random Forest reduces overfitting by averaging the predictions of multiple trees.

• Decision Tree can be prone t...read more

ETL stands for Extract, Transform, Load. It is a process of extracting data from various sources, transforming it into a usable format, and loading it into a target database.

• ETL tools include Informatica PowerCenter, Talend, Apache Nifi, Microsoft SQL Server Integration Services (SSIS), and IBM InfoSphere DataStage.

• Extract: Data is extracted from various sources such as databases, files, APIs, etc.

• Transform: Data is cl...read more