Sabudh Foundation Data Science Intern Interview Questions and Answers

Q1. Complexity of binary search
Ans. 
Binary search is a logarithmic time complexity algorithm used to search for a target value in a sorted array.
• Binary search divides the array in half at each step, reducing the search space by half each time.

• Time complexity of binary search is O(log n) where n is the number of elements in the array.

• Example: Searching for value 5 in array [1, 3, 5, 7, 9] would take 2 steps in binary search.
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Q2. Some questions were from ml, ai
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Total 50 questions,some form time and work,logical reasoning,blood relationship,directions

Q1. Tell us about yourself
Ans. 
I am a data science enthusiast with a strong background in statistics and machine learning.
• Completed coursework in data analysis, statistical modeling, and machine learning

• Proficient in programming languages such as Python, R, and SQL

• Experience with data visualization tools like Tableau and Power BI

• Worked on projects involving predictive modeling and data mining
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Q2. Which color do you like and why ?
Ans. 
I like the color blue because it reminds me of the ocean and brings a sense of calmness and tranquility.
• Blue is associated with peace, tranquility, and relaxation

• It is often used in interior design to create a calming atmosphere

• Examples: blue sky, blue ocean, blue flowers
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Aptiude Test is very easy it contains 50 questions

Q1. In technical internview basic questions about machine learning and Mathematics
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Q2. Linear and Logistic Regression
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Q3. Bernoulli Distribution
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Q4. Python build in data types
Ans. 
Python has several built-in data types including numeric, sequence, mapping, and set types.
• Numeric types include integers, floats, and complex numbers.

• Sequence types include lists, tuples, and strings.

• Mapping types include dictionaries.

• Set types include sets and frozensets.

• Each data type has its own set of methods and operations.

• Examples: int(5), float(3.14), complex(2+3j), list([1,2,3]), tuple((1,2,3)), str('hello'), ...read more
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