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I applied via Job Portal and was interviewed in Aug 2024. There was 1 interview round.
Easy one practice rs agarwal
I applied via Campus Placement and was interviewed in Aug 2022. There were 2 interview rounds.
Case study on Power BI + SQL
Seeking new challenges and growth opportunities
Desire for professional growth and development
Looking for new challenges and experiences
Seeking a better work-life balance
Company restructuring or changes in management
I moved into Data Analytics to leverage my analytical skills and passion for uncovering insights from data.
Passion for uncovering insights from data
Strong analytical skills
Interest in utilizing data to drive business decisions
I was interviewed in Aug 2021.
Round duration - 60 minutes
Round difficulty - Medium
Technical round with questions on Python, basic coding questions and Machine Learning.
Given an alphabetical string S
, determine whether it is a palindrome. A palindrome is a string that reads the same backward as forward.
The first line contains an integer ...
Check if a given string is a palindrome or not.
Iterate through the string from both ends and compare characters.
If all characters match, the string is a palindrome.
Consider handling cases where spaces or special characters are present.
Example: 'racecar' is a palindrome, 'hello' is not.
Calculate the Nth term of the Fibonacci series, denoted as F(n), using the formula: F(n) = F(n-1) + F(n-2)
where F(1) = 1
and F(2) = 1
.
The first line of each test...
Calculate the Nth term of the Fibonacci series using a recursive formula.
Use recursion to calculate the Nth Fibonacci number by summing the previous two numbers.
Base cases are F(1) = 1 and F(2) = 1.
Handle edge cases like N = 1 separately.
Optimize the solution using memoization to avoid redundant calculations.
Ensure the input N is within the constraints 1 ≤ N ≤ 10000.
You can extract the month and year from a date column in Pandas using the dt accessor.
Use the dt accessor to access the date components
Use dt.month to extract the month and dt.year to extract the year
Example: df['date_column'].dt.month will give you the month values
Example: df['date_column'].dt.year will give you the year values
R-squared measures the goodness of fit of a regression model, while p-value indicates the significance of the relationship between the independent variable and the dependent variable.
R-squared is a measure of how well the independent variable(s) explain the variability of the dependent variable in a regression model.
A high R-squared value close to 1 indicates a good fit, meaning the model explains a large portion of th...
Underfitting and overfitting are common problems in machine learning where the model is either too simple or too complex.
Underfitting occurs when the model is too simple to capture the underlying patterns in the data.
Overfitting occurs when the model is too complex and learns noise in the training data as if it were a pattern.
Underfitting can be addressed by increasing the model complexity or adding more features.
Overf...
A confusion matrix is a table that is often used to describe the performance of a classification model.
It is a matrix with rows representing the actual class and columns representing the predicted class.
It helps in evaluating the performance of a classification model by showing the number of correct and incorrect predictions.
It is commonly used in machine learning and statistics to assess the quality of a classificatio...
Random Forest is an ensemble learning method that builds multiple decision trees and combines their predictions, while XGBoost is a gradient boosting algorithm that builds trees sequentially.
Random Forest builds multiple decision trees independently and combines their predictions through averaging or voting.
XGBoost builds trees sequentially, with each tree correcting errors made by the previous ones.
Random Forest is le...
Tip 1 : Must do Previously asked Interview as well as Online Test Questions.
Tip 2 : Go through all the previous interview experiences from Codestudio and Leetcode.
Tip 3 : Do at-least 2 good projects and you must know every bit of them.
Tip 1 : Have at-least 2 good projects explained in short with all important points covered.
Tip 2 : Every skill must be mentioned.
Tip 3 : Focus on skills, projects and experiences more.
I applied via Ion and was interviewed in Nov 2021. There were 3 interview rounds.
Tredence interview questions for designations
I applied via Campus Placement and was interviewed in Apr 2021. There were 4 interview rounds.
Get interview-ready with Top Tredence Interview Questions
I applied via LinkedIn and was interviewed in Apr 2021. There were 5 interview rounds.
I was interviewed before May 2021.
Round duration - 60 minutes
Round difficulty - Medium
Test was online and can give the test anytime as per your convenience but before the deadline. Most of the questions were aptitude type and few were related to basic programming skills.
Round duration - 30 minutes
Round difficulty - Medium
I was given with a guesstimate problem and 20 mins to solve the problem where I had to mention my approach and all the assumptions in a piece of paper. Then it was a face to face interview regarding the guesstimate asking the assumptions, approach and alternate ways of solving the problem and some puzzles.
Tip 1 : Practice puzzles, guesstimates. First try on your own without looking at the solution and then check the solution see where you are going wrong and focus on that.
Tip 2 : Structured problem solving is very important while solving guesstimates/ case studies - this is the main thing the interviewer looks for
Tip 3 : SQL and Python are not mandatory but those are good to have skills
Tip 1 : Mention projects have worked on and skills you know. If you don't have any technical skills, that's fine for fresher and focus on your problem solving skills.
Tip 2 : If you have time, do some projects on SQL/Python on data analysis again in a structured way
Top trending discussions
I am a business analyst with experience in data analysis and project management.
I have a degree in business administration
I have worked with various industries including healthcare and finance
I am skilled in data visualization and reporting
I have experience in leading cross-functional teams
I am proficient in SQL and Excel
My area of interest is data analysis and visualization.
I enjoy working with large datasets and finding insights through data analysis.
I have experience using tools such as Excel, Tableau, and Python for data analysis and visualization.
I am interested in exploring new data sources and learning new techniques for data analysis.
For example, I recently worked on a project analyzing customer behavior data for a retail compa...
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1 Interview rounds
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