Altimetrik Data Science Intern Interview Questions and Answers

In both aptitude and coding in the second round, aptitude mostly consists of basic problems and there are some data science problems like bias, stats and probability.

2 coding problems the ones I got are easier didn't take more than 15 minutes to solve both of them.

Q1. Pretty hard technical interview from formulae behind algorithms to math to algorithms touched the sight of all basic data science questions that are supposed to be asked on data science interview
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Q2. What is gradient descent, why does gradient descent follow tan angles and please explain and write down the formula of it.
Ans. 
Gradient descent is an optimization algorithm used to minimize the cost function of a machine learning model.
• Gradient descent is used to update the parameters of a model to minimize the cost function.

• It follows the direction of steepest descent, which is the negative gradient of the cost function.

• The learning rate determines the step size of the algorithm.

• The formula for gradient descent is: theta = theta - alpha * (1/...read more
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Q1. Managerial Technical round asked some basic level coding questions and data handling with lists, tuples, sets and dicts.
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Q2. Please write a dictionary and try to sort it.
Ans. 
A dictionary sorted in ascending order based on keys.
• Create a dictionary with key-value pairs

• Use the sorted() function to sort the dictionary based on keys

• Convert the sorted dictionary into a list of tuples

• Use the dict() constructor to create a new dictionary from the sorted list of tuples
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Q1. What is your family background?
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Q2. Why should we hire you?
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Q3. Where do you see yourself in 5 years?
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Q4. Why are you looking for a change?
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Q5. What are your strengths and weaknesses?
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Q6. Tell me about yourself.
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