Indian Institute of Technology (IIT), Chennai
Chennai, Tamil Nadu
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Filter interviews byIndian Institute of Technology (IIT), Chennai Placement Interview Questions
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4 Dec 2024
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I applied via Campus Placement and was interviewed in Dec 2016.
6 Interview Rounds
Interview Questions
- Q1. Walk us through your resume
- Q2. Why analytics?
- Q3. Explain the concept of hypothesis testing intuitively using distribution curves for null and alternate hypotheses
- Q4. A simple probability puzzle was asked
- Q5. How can a string be reversed without affecting memory size?
- Q6. What is gradient boosting?
- Q7. What is the difference between XGBoost and AdaBoost algorithms?
- Q8. Explain one interesting project on your resume which is relevant to the profile
- Q9. What would you do if the training data is skewed?
- Q10. What is principal component analysis? When would you use it?
- Q11. What is the cost function for linear and logistic regression?
- Q12. What is regularization? Why is it used?
- Q13. Why do you think the objective of predictive modeling is minimizing the cost function? How would you define a cost function after all?
- Q14. Why our company and why not masters in data science?
Interview Preparation Tips
Round: Resume Shortlist
Experience: CGPA and background in data science were considered
Round: Test
Experience: We did not have a test as the company registered late. But from next time, they are definitely going to conduct a test. One can expect questions on probability and machine learning.
Duration: 1 hour
Round: Technical Interview
Experience: Any technical interview would mostly start with "walk us through your resume". The rest of the interview depends on how you drive their focus on to your spikes in resume. I was the winner/finalist in three pan-India data science competitons and authored a techinal paper on machine learning/ predictive modeling. I was asked to explain my approaches and the math/principle behind the working of Random forests, differences between XG Boost and Adaboost algorithms. You can expect these kind of questions if you mention such algorithms.
Tips: Know your resume inside-out. If you mention courses like machine learning or time-series analysis, you will be asked to explain algorithms using math equations. If you mention programming languages you will be asked to write a code.
Do not forget to ask questions at the end of the interview. It is the golden opportunity to gain brownie points.
Round: Technical + HR Interview
Experience: They asked me to start off by explaining any one of the projects that are relevant to the profile. While I was explaining, they asked many questions on data preprocessing, model building and model validation techniques. Later, I was asked three puzzles on probability and number theory. Then I was asked typical HR questions like "Why our company?". They asked me if I would consider pursuing masters in data science.
Tips: The amount of grilling is directly proportional to the stuff on your resume. Since I had competitions and a publication, I was properly grilled on basics of ML. But, this is not the case with other selected candidates. However, you would be definitely asked many questions/puzzles on probability.
Confidence and attitude are the major qualities you need to carry with you while attending an interview. Be firm with your answers. They should be simple and to the point. Make sure that your answers to questions like "tell us about yourself" and "walk us through your resume" are open-ended. You should leave hints about your spikes and then the interviewer comes in your way asking questions on your spikes.
Skills: Probability And Statistics, Machine Learning, Basic Coding
College Name: IIT Madras
Experience: CGPA and background in data science were considered
Round: Test
Experience: We did not have a test as the company registered late. But from next time, they are definitely going to conduct a test. One can expect questions on probability and machine learning.
Duration: 1 hour
Round: Technical Interview
Experience: Any technical interview would mostly start with "walk us through your resume". The rest of the interview depends on how you drive their focus on to your spikes in resume. I was the winner/finalist in three pan-India data science competitons and authored a techinal paper on machine learning/ predictive modeling. I was asked to explain my approaches and the math/principle behind the working of Random forests, differences between XG Boost and Adaboost algorithms. You can expect these kind of questions if you mention such algorithms.
Tips: Know your resume inside-out. If you mention courses like machine learning or time-series analysis, you will be asked to explain algorithms using math equations. If you mention programming languages you will be asked to write a code.
Do not forget to ask questions at the end of the interview. It is the golden opportunity to gain brownie points.
Round: Technical + HR Interview
Experience: They asked me to start off by explaining any one of the projects that are relevant to the profile. While I was explaining, they asked many questions on data preprocessing, model building and model validation techniques. Later, I was asked three puzzles on probability and number theory. Then I was asked typical HR questions like "Why our company?". They asked me if I would consider pursuing masters in data science.
Tips: The amount of grilling is directly proportional to the stuff on your resume. Since I had competitions and a publication, I was properly grilled on basics of ML. But, this is not the case with other selected candidates. However, you would be definitely asked many questions/puzzles on probability.
Confidence and attitude are the major qualities you need to carry with you while attending an interview. Be firm with your answers. They should be simple and to the point. Make sure that your answers to questions like "tell us about yourself" and "walk us through your resume" are open-ended. You should leave hints about your spikes and then the interviewer comes in your way asking questions on your spikes.
Skills: Probability And Statistics, Machine Learning, Basic Coding
College Name: IIT Madras
SUNEEL KUMAR MATAM
posted on 4 Dec 2016
I applied via Campus Placement and was interviewed in Dec 2016.
5 Interview Rounds
Interview Questions
- Q1. Explain neural networks, backpropagation?
- Q2. Why not higher studies? Questions on technical details of project
Interview Preparation Tips
Round: Resume Shortlist
Experience: Apart from resume shortlist, there was a preliminary interview to know your experience in analytics. Some probability questions were asked
Tips: Prepare probablity and stat.
Round: Technical + HR Interview
Experience: Probability and statistics questions. Be able to explain projects thoroughly.
Tips: Be well prepared with resume points.
Skills: Analytics And Coding
College Name: IIT Madras
Experience: Apart from resume shortlist, there was a preliminary interview to know your experience in analytics. Some probability questions were asked
Tips: Prepare probablity and stat.
Round: Technical + HR Interview
Experience: Probability and statistics questions. Be able to explain projects thoroughly.
Tips: Be well prepared with resume points.
Skills: Analytics And Coding
College Name: IIT Madras
I applied via Campus Placement and was interviewed in Dec 2016.
4 Interview Rounds
Interview Questions
- Q1. Previous Experience in Analytics
- Q2. Technical questions about analytics
Interview Preparation Tips
Round: Resume Shortlist
Experience: CGPA shortlist
College Name: IIT Madras
Experience: CGPA shortlist
College Name: IIT Madras
Shyam Krishna Sannapaneni
posted on 4 Dec 2016
I applied via Campus Placement and was interviewed in Jan 2016.
5 Interview Rounds
Interview Questions
- Q1. What is your previous experience in Data Analytics?
- Q2. Technical questions about Data analytics
Interview Preparation Tips
Round: Resume Shortlist
Experience: CG shortlist
College Name: IIT Madras
Experience: CG shortlist
College Name: IIT Madras
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