Rapido Interview Questions, Process, and Tips for Freshers

Q1. Why should u want to join here
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Q2. What Is your qualification and why do u choose customer care executive
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Q1. Did you know marketing operations
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Q2. Did you know rapido
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MCQ based of loops, iteration, pseudocode, SQL and debugging were asked. 30 questions in total and fairly easy. 1 hour duration and I attempted about 20 questions. No negative marking. It was conducted on HackerEarth platform.

Q1. 1. Tell me about yourself
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Q2. 2. Basic Statistical Questions > mean, median, mode > data cleaning process. > how do you treat missing values? > what are joins and give an application of joins in data? > what are views in sql? > explain...read more
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Q3. 3. Execute a SQL query to get the top second row.
Ans. 
SQL query to get the second row from the top.
• Use the LIMIT keyword to limit the number of rows returned.

• Use the OFFSET keyword to skip the first row.

• Order the rows by a column to ensure consistent results.
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Q4. 4. Difference between DBMS and RDBMS
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DBMS is a software system to manage databases, while RDBMS is a type of DBMS that uses a relational model.
• DBMS stands for Database Management System, while RDBMS stands for Relational Database Management System.

• DBMS can manage any type of database, while RDBMS uses a specific model based on tables, keys, and relationships.

• DBMS is less strict in terms of data integrity, while RDBMS enforces strict rules to ensure data c...read more
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Q5. 5. What are stored procedures and when are they used?
Ans. 
Stored procedures are pre-written SQL codes that can be saved and reused. They are used to improve performance and security.
• Stored procedures are used to reduce network traffic by executing a batch of SQL statements at once.

• They can improve performance by reducing the amount of time spent parsing and optimizing SQL statements.

• Stored procedures can also enhance security by allowing access to only specific parts of the d...read more
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Q1. 1. Tell me about yourself
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Q2. 2. Explain the data process in your project
Ans. 
The data process in my project involves data collection, cleaning, analysis, and visualization.
• Data collection involved gathering data from various sources such as surveys, databases, and APIs.

• Data cleaning was done to remove duplicates, missing values, and outliers.

• Data analysis was performed using statistical methods and machine learning algorithms.

• Data visualization was used to present the findings in a clear and co...read more
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Q3. 3. What was the finding from the project?
Ans. 
The finding from the project was that there is a strong correlation between customer satisfaction and repeat purchases.
• The project analyzed customer satisfaction surveys and purchase data

• The data showed that customers who reported high satisfaction scores were more likely to make repeat purchases

• This finding suggests that improving customer satisfaction can lead to increased customer loyalty and revenue
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Q4. 4. A case study based on hypothesis testing and its application
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Q5. 5. Name three things that your learnt from your Data Science and Analytics course.
Ans. 
Three things I learned from my Data Science and Analytics course are statistical analysis, data visualization, and machine learning.
• Statistical analysis: Learned how to use statistical methods to analyze data and draw conclusions.

• Data visualization: Learned how to create visual representations of data to better understand patterns and trends.

• Machine learning: Learned how to use algorithms to build predictive models and
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Test duration of 1 hour based on probability and control statements

Q1. Ml algorithms that you have prior knowledge about
Ans. 
I have prior knowledge about various machine learning algorithms.
• Linear Regression

• Logistic Regression

• Decision Trees

• Random Forests

• Support Vector Machines

• Naive Bayes

• K-Nearest Neighbors

• Gradient Boosting

• Neural Networks
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Q2. Data visualization techniques you have studied and used
Ans. 
I have studied and used various data visualization techniques including bar charts, line graphs, scatter plots, and heat maps.
• I have experience creating bar charts to compare data across categories

• I have used line graphs to show trends over time

• I have created scatter plots to identify correlations between variables

• I have used heat maps to visualize data density and identify patterns
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