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Wolters Kluwer Data Science Intern Interview Questions and Answers
Wolters Kluwer Data Science Intern Interview Experiences
1 interview found
I applied via Referral and was interviewed in Dec 2023. There was 1 interview round.
(7 Questions)
- Q1. Tell me about yourself
- Q2. Tell me in details about your project. (Mainly the python related project)
- Q3. Which ML algorithm did you use in your project?
- Ans.
I used the Random Forest algorithm in my project.
Random Forest is an ensemble learning method that combines multiple decision trees to make predictions.
It is used for both classification and regression tasks.
Random Forest reduces overfitting and provides feature importance.
Example: I used Random Forest to predict customer churn in a telecom company.
- Q4. What is Sql? And what is a database?
- Ans.
SQL is a programming language used for managing and manipulating relational databases. A database is a structured collection of data.
SQL is used to retrieve, insert, update, and delete data from a database.
A database is a software system that stores and organizes data in a structured manner.
SQL allows users to define the structure of a database, create tables, and establish relationships between tables.
Examples of data
- Q5. What do you understand by joins in sql?
- Ans.
Joins in SQL are used to combine rows from two or more tables based on a related column between them.
Joins are used to retrieve data from multiple tables in a single query.
Common types of joins include inner join, left join, right join, and full outer join.
Joins are performed using the JOIN keyword and specifying the columns to join on.
Joins can be used to combine tables based on matching values or non-matching values.
...
- Q6. Apply join in the above tables (Table was provided by the interviewer)
- Q7. How many squares are their in a chess box? (Aptitude question)
Interview Preparation Tips
- Python
- Machine Learning
- Natural Language Processing
- MySQL
- Algorithms
Skills evaluated in this interview
Interview questions from similar companies
Abhilasha Dimble
I applied via Naukri.com and was interviewed in Jan 2024. There was 1 interview round.
(1 Question)
- Q1. Asked about projects. What is classification? Is knn used for regression?how? decision tree working for regression and classification Is naive Bayes used for regression?how? LLM Docker Aws GenAI Code for ...
Interview Preparation Tips
Starts interview with lots of questions..
He interrupts me in every question's answer.. doesn't even ready listen my answers ...
I applied via Approached by Company and was interviewed in Aug 2023. There was 1 interview round.
(1 Question)
- Q1. How can Logistic regression be applied for multiclasstext classification
- Ans.
Logistic regression can be applied for multiclasstext classification by using one-vs-rest or softmax approach.
One-vs-rest approach: Train a binary logistic regression model for each class, treating it as the positive class and the rest as the negative class.
Softmax approach: Use the softmax function to transform the output of the logistic regression into probabilities for each class.
Evaluate the model using appropriate...
Skills evaluated in this interview
Selected
I applied via LinkedIn and was interviewed before Apr 2023. There was 1 interview round.
(1 Question)
- Q1. How does fbpropher forecasting model works and how is can be used to forecsst trafffic
- Ans.
fbprophet is a forecasting model developed by Facebook that uses time series data to make predictions.
fbprophet is an open-source forecasting tool developed by Facebook's Core Data Science team.
It is based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.
fbprophet can be used to forecast traffic by providing historical data on traffic patterns and usi...
Interview Preparation Tips
Data Scientist Interview Questions & Answers
Automatic Data Processing (ADP)
Anonymous
posted on 21 Oct 2022
I applied via Approached by Company and was interviewed in Sep 2022. There were 3 interview rounds.
(1 Question)
- Q1. Basic DS question like how to handle missing features
(1 Question)
- Q1. Case study based questions
Interview Preparation Tips
Selected
I applied via Company Website and was interviewed in Dec 2024. There were 3 interview rounds.
Basic self evaluation test.
(3 Questions)
- Q1. What project I have completed and follow-up questions on that?
- Q2. How to handle class imbalance.
- Ans.
Handling class imbalance involves techniques like resampling, using different algorithms, and adjusting class weights.
Use resampling techniques like oversampling or undersampling to balance the classes.
Utilize algorithms that are robust to class imbalance, such as Random Forest, XGBoost, or SVM.
Adjust class weights in the model to give more importance to minority class.
Use evaluation metrics like F1 score, precision, r...
- Q3. Basic Python coding questions.
(2 Questions)
- Q1. Data-related questions.
- Q2. ML Ops questions.
Interview Preparation Tips
- Python
- MLOPS
I appeared for an interview in Feb 2017.
Interview Questionnaire
4 Questions
- Q1. Everything related to previous projects.
- Q2. Normalization of database to BCNF
- Ans.
Normalization to BCNF ensures that every non-trivial functional dependency is satisfied.
Identify all functional dependencies
Eliminate partial dependencies
Eliminate transitive dependencies
Ensure every determinant is a candidate key
- Q3. Difference between 'having' clause and 'where' clause in MySQL
- Ans.
HAVING clause is used with GROUP BY to filter groups, WHERE clause is used to filter rows.
HAVING clause is used with GROUP BY clause to filter groups based on aggregate functions.
WHERE clause is used to filter rows based on conditions.
HAVING clause is used after GROUP BY clause, while WHERE clause is used before GROUP BY clause.
HAVING clause can use aggregate functions, while WHERE clause cannot.
Example: SELECT categor...
- Q4. DBMS queries
Interview Preparation Tips
Experience: It was 1-to-1 interview where I was asked about the previous projects first. They have asked everything about the project, from why we chose the technology we chose and how we implemented it.
Tips: Can't give much tips as I have not faced many interviews myself, but as far as internship interviews go, they require candidates who are willing to learn. You don't need to convince them that you know everything, as the basic understanding of the subject and willingness to learn will do just fine.
Round: Test
Duration: 20 minutes
Total Questions: 25
College Name: PDPM IIITDM, Jabalpur
Skills evaluated in this interview
Interview Questionnaire
3 Questions
- Q1. There are 1 million random numbers and 1 number is missing find the missing number
- Ans.
Find the missing number from 1 million random numbers.
Calculate the sum of all numbers from 1 to 1 million using the formula n(n+1)/2
Calculate the sum of all the given numbers
Subtract the sum of given numbers from the sum of all numbers to get the missing number
- Q2. Algorithm and complexities
- Q3. Basic technical questions
Skills evaluated in this interview
I applied via Referral and was interviewed in Mar 2020. There were 5 interview rounds.
Interview Questionnaire
4 Questions
- Q1. Projects, Out of box thinking
- Q2. Few significant accomplishments in previous companies
- Ans.
Implemented data-driven strategies to increase revenue by 15% in previous company.
Developed predictive models to optimize pricing strategies
Identified key customer segments for targeted marketing campaigns
Automated data collection and analysis processes for efficiency
Collaborated with cross-functional teams to implement data-driven decisions
- Q3. Tools and technologies
- Q4. Case study. Problem statement given and asked to provide a solution
Interview Preparation Tips
I applied via Campus Placement and was interviewed in Sep 2023. There was 1 interview round.
KPI's for the ecommerce industries
Interview Preparation Tips
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