Relanto Global Interview Questions and Answers

General Aptitude and Data Related Questions

Simple 1 DSA coding question

Shortlisted students will have GD

Q1. Why did you learn DSA
Ans. 
Learned DSA to improve problem-solving skills and prepare for technical interviews.
• To improve problem-solving skills

• To prepare for technical interviews

• To understand efficient algorithms and data structures

• To enhance coding abilities
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Q2. What is the need of inheritance
Ans. 
Inheritance allows for code reusability, promotes code organization, and enables polymorphism.
• Allows for code reusability by inheriting attributes and methods from a parent class

• Promotes code organization by creating a hierarchy of classes

• Enables polymorphism, where objects of different classes can be treated as objects of a common superclass

• Example: A 'Vehicle' class can be inherited by 'Car' and 'Truck' classes, inhe...read more
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Q3. 4 complex SQL queries
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Q4. Questions related to my projects
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Q5. Explain Random Forest Regression algorithm
Ans. 
Random Forest Regression is an ensemble learning algorithm that uses multiple decision trees to make predictions.
• Random Forest Regression combines multiple decision trees to reduce overfitting and improve accuracy.

• Each tree in the random forest is trained on a random subset of the data and features.

• The final prediction is the average of predictions from all the trees in the forest.

• Random Forest Regression is used for p...read more
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Brush up your skills on aptitude questions this won't be tough

Q1. Question are based on your field of expertise
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Q2. Have a good knowledge of excel
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Q1. Tell me about your self
Ans. 
I am a data analyst with a strong background in statistics and programming. I have experience in analyzing large datasets and providing actionable insights.
• Proficient in statistical analysis and data visualization tools such as Python, R, and Tableau

• Skilled in SQL for data extraction and manipulation

• Experience in conducting A/B testing and hypothesis testing

• Strong problem-solving and critical thinking skills

• Effective c...read more
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Q2. Tell me about your project that you have done
Ans. 
Developed a predictive model to forecast customer churn in a telecommunications company.
• Used machine learning algorithms such as logistic regression and random forest.

• Performed data preprocessing, feature engineering, and model evaluation.

• Achieved an accuracy of 85% in predicting customer churn.

• Implemented the model in Python using libraries like pandas, scikit-learn, and matplotlib.
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