Tredence Data Science Associate Interview Questions and Answers

Data Structure medium level questions. Approach important rather final results. Basic understanding of coding.

Q1. Coding, data filtering, Machine Learning and Statistics
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Q1. Machine learning project discussion and your approach.
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Q1. Job description, salary discussion and miscellaneous
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Python Coding Questions Revolve around 1 basic and 1 medium level of python and 1-2 Sql Question and MCQ based On Stats, Data Science related topics

Q1. Please be Prepared to Discuss Your Experience or the Projects you mentioned on the resume?And why i you have selected this algorithm and all related question related to why?
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Q2. Whats the evaluation mertics for classification and regression model?bias and variance
Ans. 
Evaluation metrics for classification and regression models are different. Bias and variance are important factors to consider.
• Classification metrics include accuracy, precision, recall, F1 score, ROC curve, and AUC.

• Regression metrics include mean squared error, mean absolute error, R-squared, and adjusted R-squared.

• Bias refers to the difference between the predicted values and the actual values, while variance refers ...read more
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Q3. What are decision Trees and All the algorithms that you have used in ur project?
Ans. 
Decision Trees are a type of supervised learning algorithm used for classification and regression tasks.
• Decision Trees are used to create a model that predicts the value of a target variable based on several input variables.

• The algorithm splits the data into subsets based on the most significant attribute and continues recursively until a leaf node is reached.

• Some of the algorithms used in my project include Random For...read more
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Q1. Hr will discuss your salary with you and try to get it as high as possible
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Q2. They will pressurize to join the company as soon as possible such is their tactics
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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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There are 20 Aptitude Question (time to solve these 20 question is 30 minutes). Then 10 MCQ Questions on Computer Science Fundamentals (time 10 minutes).

There are 5 question based on DSA 3 question of 20 marks and 2 questions of 50 marks. You need to any two question of 20 marks questions and one of 50 marks question. Total time you get to solve these question is 60 minutes.

Q1. Get Second highest element from an array (duplicates elements are allowed). Required T.C-->O(N) Single traversal. S.C--->O(1)
Ans. 
Get second highest element from an array of strings with O(N) time complexity and O(1) space complexity.
• Initialize two variables to store the highest and second highest elements.

• Traverse the array and update the variables accordingly.

• Return the second highest element.

• Handle edge cases like empty array or array with only one element.
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Q2. Sort nearly sortes array.
Ans. 
Sort nearly sorted array using min heap
• Create a min heap of size k+1

• Insert first k+1 elements into min heap

• For remaining elements, extract min and insert new element

• Extract all remaining elements from min heap

• Time complexity: O(nlogk)

• Example: ['apple', 'banana', 'cherry', 'date', 'elderberry']
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Q3. Coffiecent of x^7 in equation ? y=(x^101-1)(x^100+1)(x^99-1)...........................................(X^0+1)
Ans. 
Coffiecent of x^7 in a given equation
• Use the binomial theorem to expand the equation

• Identify the term with x^7

• The coefficient of x^7 is the coefficient of that term
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Q4. Some more probabilty and statistic questions exactly didn't remember.
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