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40+ Parcham Classes Interview Questions and Answers

Updated 14 Jan 2025
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Q1. Rotate array

Given an array with N elements, the task is to rotate the array to the left by K steps, where K is non-negative.

Input Format:

The first line contains an integer N representing the size of the array...read more
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Q2. How will you solve a trans-shipment problem in excel solver software?

Ans.

Trans-shipment problem can be solved in Excel Solver by setting up a linear programming model.

  • Define decision variables for the amount of goods to be shipped between each pair of locations.

  • Set up constraints to ensure that the supply and demand at each location are met.

  • Add constraints to limit the amount of goods that can be shipped through intermediate locations.

  • Define the objective function to minimize the total cost of shipping.

  • Use Excel Solver to find the optimal solution...read more

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Q3. Geeks for geeks puzzles 1. How many parts are divided with one circle & 4 lines.

Ans.

The number of parts divided by one circle and four lines is 11.

  • Each line intersects with every other line and the circle.

  • Each intersection point creates a new part.

  • The circle itself also counts as a part.

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Q4. What is your area of interest?

Ans.

My area of interest is artificial intelligence and machine learning.

  • I am fascinated by the potential of AI and ML to revolutionize various industries.

  • I enjoy exploring the latest advancements in deep learning and natural language processing.

  • I am particularly interested in the ethical implications of AI and the need for responsible development.

  • Some of my favorite examples of AI in action include self-driving cars, virtual assistants, and image recognition technology.

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Q5. Explain transportation problem.

Ans.

Transportation problem is a linear programming problem that deals with minimizing the cost of transporting goods from sources to destinations.

  • It involves determining the optimal way to transport goods from sources to destinations

  • It considers factors such as cost, capacity, and demand

  • It can be solved using various methods such as the North-West Corner Method, Least Cost Method, and Vogel's Approximation Method

  • Example: A company needs to transport goods from three factories to ...read more

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Q6. Tell me about some joins in SQL.

Ans.

Joins in SQL are used to combine rows from two or more tables based on a related column between them.

  • Types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

  • INNER JOIN returns rows when there is at least one match in both tables.

  • LEFT JOIN returns all rows from the left table and the matched rows from the right table.

  • RIGHT JOIN returns all rows from the right table and the matched rows from the left table.

  • FULL JOIN returns rows when there is a match in one of t...read more

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Q7. What was your GRE score?

Ans.

I did not take the GRE exam.

  • I did not apply for a program that required GRE scores.

  • My focus was on gaining practical experience through internships and projects.

  • I have excelled in my academic and professional pursuits without a GRE score.

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Q8. Puzzle: Given a dice with only 2 possible outcomes 1 & 3 and with probabilities 1/3 and 2/3 respectively. What will you do so that the dice can be used for tossing(in tossing, we expect unbiased outcomes).

Ans.

Label the outcomes as 0 and 1. Toss the dice twice and record the outcome as 00, 01, 10, or 11. If the outcome is 00 or 11, discard and repeat.

  • Label the outcomes as 0 and 1

  • Toss the dice twice and record the outcome as 00, 01, 10, or 11

  • If the outcome is 00 or 11, discard and repeat

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Q9. How was CAT?

Ans.

CAT was challenging but I managed to do well.

  • CAT was a difficult exam but I prepared well for it.

  • I had to manage my time effectively during the exam.

  • I am confident that I did well in the exam.

  • The exam tested my analytical and problem-solving skills.

  • Overall, I am satisfied with my performance in CAT.

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Q10. Analytical approach towards daily tasks

Ans.

I approach daily tasks analytically by breaking them down into smaller steps and using data-driven decision making.

  • I start by clearly defining the task and its objectives.

  • I gather relevant data and information to understand the problem or task at hand.

  • I break down the task into smaller, manageable steps or sub-tasks.

  • I prioritize the steps based on their importance and urgency.

  • I use data analysis techniques to identify patterns, trends, and insights.

  • I make data-driven decision...read more

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Q11. Do you know about OOP?

Ans.

Yes, Object-Oriented Programming (OOP) is a programming paradigm based on the concept of objects, which can contain data and code.

  • OOP focuses on creating objects that interact with each other to solve problems

  • Key principles of OOP include encapsulation, inheritance, and polymorphism

  • Examples of OOP languages include Java, C++, and Python

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Q12. How to check for multicollinearity

Ans.

Multicollinearity can be checked using correlation matrix, variance inflation factor (VIF), and eigenvalues.

  • Calculate the correlation matrix between independent variables. High correlation coefficients indicate multicollinearity.

  • Calculate the VIF for each independent variable. VIF values above 10 indicate multicollinearity.

  • Check for multicollinearity using eigenvalues of the correlation matrix. If there are eigenvalues close to zero, it indicates multicollinearity.

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Q13. explain svm algorithm in you project

Ans.

SVM algorithm is a supervised machine learning model used for classification and regression tasks by finding the optimal hyperplane.

  • SVM stands for Support Vector Machine

  • It works by finding the hyperplane that best separates the classes in the feature space

  • It can handle both linear and non-linear data by using different kernels like linear, polynomial, and radial basis function

  • SVM aims to maximize the margin between the classes to improve generalization

  • It is commonly used in i...read more

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Q14. why you studied data science

Ans.

Passion for solving complex problems with data-driven insights

  • Fascination with the power of data to drive decision-making

  • Interest in leveraging statistical analysis and machine learning algorithms

  • Desire to make a positive impact through data-driven solutions

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Q15. difference between sql and no sql

Ans.

SQL is a traditional relational database management system, while NoSQL is a non-relational database system.

  • SQL is structured query language used for relational databases

  • NoSQL is a non-relational database system that can handle unstructured data

  • SQL databases are table-based, NoSQL databases are document, key-value, graph, or wide-column stores

  • SQL is good for complex queries and transactions, NoSQL is better for large amounts of data and scalability

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Q16. What is R2 score

Ans.

R2 score is a statistical measure that represents the proportion of the variance in the dependent variable that is predictable from the independent variable(s).

  • R2 score ranges from 0 to 1, with 1 indicating a perfect fit.

  • It is often used in regression analysis to evaluate the goodness of fit of a model.

  • R2 score can be interpreted as the percentage of the response variable variation that is explained by a linear model.

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Q17. A plane is 200Km away from its destination and starts to descend. What would be the angle at which the plane descends? (Guesstimates)

Ans.

The angle at which the plane descends cannot be accurately determined without additional information.

  • The angle of descent depends on the rate of descent and the distance remaining to the destination.

  • The weight of the plane, wind speed and direction, and other factors can also affect the angle of descent.

  • Without knowing the rate of descent or the remaining distance, it is impossible to accurately estimate the angle of descent.

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Q18. explain 4 pillars of oops

Ans.

The 4 pillars of OOP are encapsulation, inheritance, polymorphism, and abstraction.

  • Encapsulation: Bundling data and methods that operate on the data into a single unit.

  • Inheritance: Ability of a class to inherit properties and behavior from another class.

  • Polymorphism: Ability to present the same interface for different data types.

  • Abstraction: Hiding the complex implementation details and showing only the necessary features.

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Q19. Guesstimate: Estimate the quantity of detergent used in india in 1 year.

Ans.

Approximately 2 million metric tons of detergent is used in India annually.

  • Consider the population of India and the average usage of detergent per person.

  • Factor in the usage of detergent in industries and commercial establishments.

  • Take into account the different types of detergents used for various purposes.

  • Refer to market research reports for more accurate data.

  • Assume a growth rate in detergent usage based on population and economic growth.

  • Approximately 2 million metric tons...read more

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Q20. Estimate the size of racks of rice in a store in any area

Ans.

The size of racks of rice in a store can vary depending on the store's location, size, and target market.

  • The size of the store can determine the size of the racks

  • The target market can determine the quantity of rice sold and therefore the size of the racks

  • The location of the store can determine the size of the racks based on the available space

  • The type of rice sold can also determine the size of the racks

  • Observation of similar stores in the area can provide an estimate

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Q21. How to deal with problems that come daily along the way

Ans.

To deal with daily problems, it is important to stay calm, prioritize tasks, seek help when needed, and learn from each experience.

  • Stay calm and composed to think clearly and make rational decisions

  • Prioritize tasks based on urgency and importance

  • Seek help from colleagues or supervisors when facing complex problems

  • Learn from each experience to prevent similar problems in the future

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Q22. Random forest vs decision tree vs xg boost

Ans.

Random forest is an ensemble method using multiple decision trees, XGBoost is a gradient boosting algorithm that builds trees sequentially.

  • Random forest is an ensemble learning method that builds multiple decision trees and combines their predictions.

  • Decision tree is a single tree model that makes decisions based on features to predict outcomes.

  • XGBoost is a gradient boosting algorithm that builds trees sequentially, optimizing the model's performance.

  • Random forest reduces ove...read more

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Q23. Difference between Delete and Truncate in SQL

Ans.

Delete removes specific rows from a table, while Truncate removes all rows from a table.

  • Delete is a DML command, while Truncate is a DDL command.

  • Delete can be rolled back, while Truncate cannot be rolled back.

  • Delete maintains the table structure and indexes, while Truncate resets the table structure and indexes.

  • Delete triggers delete triggers and delete constraints, while Truncate does not trigger any triggers or constraints.

  • Delete is slower than Truncate for large tables.

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Q24. Code any program in 2 languages

Ans.

I can code a program in Python and Java.

  • I am proficient in both Python and Java programming languages.

  • I have experience in developing web applications using Python and Java frameworks.

  • I can write efficient and optimized code in both languages.

  • I can develop programs for data analysis, machine learning, and automation using Python.

  • I can develop enterprise-level applications using Java.

  • Examples: Python - a program to scrape data from a website, Java - a program to implement a so...read more

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Q25. Culture about Axtria and policies

Ans.

Axtria promotes a collaborative and inclusive culture with a focus on innovation and growth.

  • Axtria values diversity and inclusion in the workplace

  • The company encourages innovation and creativity

  • There are policies in place to support employee growth and development

  • Axtria promotes a collaborative work environment

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Q26. Ridge and lasso regression difference

Ans.

Ridge and lasso regression are both regularization techniques used in linear regression to prevent overfitting by adding penalty terms to the cost function.

  • Ridge regression adds a penalty term equivalent to the square of the magnitude of coefficients, while lasso regression adds a penalty term equivalent to the absolute value of the magnitude of coefficients.

  • Ridge regression tends to shrink the coefficients towards zero but does not eliminate them completely, while lasso regr...read more

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Q27. Why Axtria? What you know about Axtria?

Ans.

Axtria is a leading provider of cloud-based software and data analytics solutions for the life sciences industry.

  • Axtria offers innovative solutions for commercial operations, including sales and marketing analytics, data management, and customer engagement.

  • The company has a strong focus on leveraging advanced analytics and artificial intelligence to drive business outcomes.

  • Axtria has a global presence, with offices in the US, Europe, and Asia.

  • The company has received numerous...read more

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Q28. Explain Machine learning in layman language in 2 minutes to client

Ans.

Machine learning is a type of artificial intelligence that allows computers to learn and improve from experience without being explicitly programmed.

  • Machine learning is like teaching a computer to recognize patterns and make decisions based on data.

  • It involves algorithms that analyze data, identify patterns, and make predictions or decisions.

  • Examples include recommendation systems like Netflix suggesting movies based on your viewing history, or self-driving cars learning to n...read more

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Q29. Any questions?

Ans.

Yes, I have a few questions regarding the role and responsibilities of a Business Analyst.

  • Can you tell me more about the company's current business processes?

  • What are the key performance indicators (KPIs) that the company tracks?

  • How does the company measure the success of a project?

  • What tools and software does the company use for data analysis?

  • Can you provide an example of a successful project that the Business Analyst team has completed?

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Q30. Assumptions of regression

Ans.

Assumptions of regression

  • Linearity: The relationship between the independent and dependent variables is linear.

  • Independence: The residuals are independent of each other.

  • Homoscedasticity: The variance of the residuals is constant across all levels of the independent variables.

  • Normality: The residuals are normally distributed.

  • No multicollinearity: The independent variables are not highly correlated with each other.

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Q31. Design the source to target mapping for given scenario, SQL, Previous Project, Data warehousing concepts, SCDs

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Q32. 1. what is sql injection ? 2.what is svm , random forest ?

Ans.

SQL injection is a type of cyber attack where malicious SQL statements are inserted into an entry field to manipulate a database.

  • SQL injection can be used to steal sensitive information or modify data in a database.

  • It can be prevented by using parameterized queries and input validation.

  • SVM (Support Vector Machine) and Random Forest are machine learning algorithms used for classification and regression tasks.

  • SVM tries to find the best hyperplane that separates data into differ...read more

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Q33. Get the latest diagnosis date of patient

Ans.

To get the latest diagnosis date of a patient

  • Query the database for the patient's diagnosis dates

  • Sort the dates in descending order to get the latest one

  • Retrieve the latest diagnosis date

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Q34. how model maintainance was done, mlflow

Ans.

Model maintenance is done using MLflow, a platform for managing the end-to-end machine learning lifecycle.

  • MLflow provides tools for tracking experiments, packaging code, and deploying models.

  • It allows for easy comparison of different model versions and tracking of performance metrics.

  • MLflow can be integrated with popular machine learning libraries like scikit-learn, TensorFlow, and PyTorch.

  • Model maintenance involves regularly updating and retraining models to ensure they rema...read more

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Q35. What are 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 based on a related column between them

  • Common types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN

  • Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column

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Q36. what is ssl layer in cn?

Ans.

SSL layer in CN refers to the use of Secure Sockets Layer to encrypt data transmitted over a network.

  • SSL layer provides secure communication between client and server

  • It uses encryption to protect data from unauthorized access

  • CN refers to Common Name in SSL certificate

  • SSL layer is now replaced by TLS (Transport Layer Security)

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Q37. what are complex mapping you built

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Q38. What is exp in pharma

Ans.

Exp refers to expiration date in the pharmaceutical industry.

  • Exp refers to the expiration date of a pharmaceutical product.

  • It is important to check the exp date before using any medication to ensure its effectiveness and safety.

  • Expired medications should be properly disposed of to avoid potential harm.

  • Manufacturers usually print the exp date on the packaging of the product.

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Q39. what is precision recalll

Ans.

Precision recall is a measure used in classification tasks to evaluate the quality of the model's predictions.

  • Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.

  • Recall is the ratio of correctly predicted positive observations to the all observations in actual class.

  • Precision and recall are often used together to evaluate the performance of a classification model.

  • For example, in a medical diagnosis scenario, precisi...read more

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Q40. how to build data pipeline

Ans.

Building a data pipeline involves extracting, transforming, and loading data from various sources to a destination for analysis.

  • Identify data sources and determine the data to be collected

  • Extract data from sources using tools like Apache NiFi or Apache Kafka

  • Transform data using tools like Apache Spark or Python scripts

  • Load data into a destination such as a data warehouse or database

  • Schedule and automate the pipeline for regular updates

  • Monitor and optimize the pipeline for per...read more

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Q41. Describe MMx process

Ans.

MMx process is a strategic marketing process that focuses on maximizing market share and profitability.

  • MMx process involves analyzing market trends and competition

  • It includes identifying target customers and developing marketing strategies to reach them

  • MMx process also involves monitoring and adjusting strategies based on performance metrics

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Q42. qns on tech tools used

Ans.

I have experience using a variety of tech tools including Microsoft Office Suite, Google Analytics, and Salesforce.

  • Microsoft Office Suite (Word, Excel, PowerPoint)

  • Google Analytics for data analysis

  • Salesforce for CRM management

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