Arintra Data Analyst Intern Interview Questions and Answers

Time series and regression

Queries and commands

It was a training+ internship

Q1. NUmber of groups and group wise projects
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Aptitude test was the basics asked in every exam

Q1. What is difference between 4stroke and 2 stroke engine?
Ans. 
4-stroke engines have 4 strokes per cycle, while 2-stroke engines have 2 strokes per cycle.
• 4-stroke engines are more fuel-efficient and produce less pollution than 2-stroke engines.

• 2-stroke engines are simpler and lighter than 4-stroke engines.

• 4-stroke engines have separate intake, compression, power, and exhaust strokes, while 2-stroke engines combine intake and compression, and power and exhaust strokes.

• Examples of 4...read more
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Q2. What is a bevel gear? Give an example
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A bevel gear is a type of gear used to transmit power between shafts at an angle.
• Bevel gears have conical shapes and are used to change the direction of rotation.

• They are commonly used in automobiles, airplanes, and power plants.

• An example of a bevel gear is the ring and pinion gear in a car's differential.

• Another example is the bevel gear used in a hand drill to transmit power from the motor to the chuck.
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Q1. Machine learning algorithms.
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Machine learning algorithms are tools used to analyze data, identify patterns, and make predictions without being explicitly programmed.
• Machine learning algorithms can be categorized into supervised, unsupervised, and reinforcement learning.

• Examples of machine learning algorithms include linear regression, decision trees, support vector machines, and neural networks.

• These algorithms require training data to learn patte...read more
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Q2. Credit risk life cycle
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Q3. Pandas related questions
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Q1. Steps of developing a credit risk model
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Developing a credit risk model involves several steps to assess the likelihood of a borrower defaulting on a loan.
• 1. Define the problem and objectives of the credit risk model.

• 2. Gather relevant data such as credit history, income, debt-to-income ratio, etc.

• 3. Preprocess the data by handling missing values, encoding categorical variables, and scaling features.

• 4. Select a suitable machine learning algorithm such as logi...read more
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Q2. Pandas related questions
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Q3. Bagging and Boosting
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Q1. Explain AIC and BIC
Ans. 
AIC and BIC are statistical measures used for model selection in the context of regression analysis.
• AIC (Akaike Information Criterion) is used to compare the goodness of fit of different models. It penalizes the model for the number of parameters used.

• BIC (Bayesian Information Criterion) is similar to AIC but penalizes more heavily for the number of parameters, making it more suitable for model selection when the focus...read more
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Q2. Difference between xgboost and lightgbm
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XGBoost is a popular gradient boosting library while LightGBM is a faster and more memory-efficient alternative.
• XGBoost is known for its accuracy and performance on structured/tabular data.

• LightGBM is faster and more memory-efficient, making it suitable for large datasets.

• LightGBM uses a histogram-based algorithm for splitting whereas XGBoost uses a level-wise tree growth strategy.
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Q3. Bagging and boosting
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Time structure is a part of Environment that used as reference to measure and keep track . The structure of the time also a central . And overall the structure of time remains of the debate.

Q1. Data Science and Programming
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Mathematics and other questions

It was okay as the interview was scheduled on time.

Q1. They asked questions in the interview Including Python, Machine learning, SQL, Power BI
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Logical reasoning, current affairs, numericals

Q1. Genuinely HR round
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