HighRadius Technical Intern Interview Questions and Answers

General DSA with some ds questions

Q1. Walk through resume
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Q2. Reverse linked list
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Q3. Use of oops in some cases
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There were DSA questions and time limit was 1 hr

Q1. Calculate factorial using tabulation
Ans. 
Factorial calculation using tabulation in dynamic programming
• Create an array to store factorial values up to n

• Initialize the array with base cases (0! = 1, 1! = 1)

• Iterate from 2 to n and calculate factorial using previous values in the array

• Return the factorial value at index n
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Q2. Wildcard matching question
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5 sections networking, os, aptitude, dbms, data structures

Q1. About resume and projects accomplished
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Q1. Tell me about your self
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Q1. Know about the process
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Q1. Mental ability check like u r capable for this role or not
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Q1. Very toughest round like overall in this round u need to tell and as well as they asked we should know properly what kind of process they r running
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Q1. Sorting algorithm
Ans. 
Sorting algorithms are used to arrange elements in a specific order.
• Sorting algorithms can be categorized as comparison-based or non-comparison-based.

• Examples of sorting algorithms include Bubble Sort, Merge Sort, and Quick Sort.

• Efficiency of sorting algorithms is measured in terms of time complexity and space complexity.
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Q2. Secod highest salary
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So total 4 coding questions 2-medium 2-hard

Q1. One-on-one round more conditional questions 4-5 technical questions
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Q2. 1os question 1dbms 1java 1cpp 1 computer network que and more situational questions
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Q3. Diff between rdbms dbms
Ans. 
RDBMS is a type of DBMS that stores data in a structured format with relationships between tables.
• RDBMS enforces ACID properties for database transactions.

• RDBMS uses SQL for querying and managing data.

• DBMS is a general term for any system that manages databases, while RDBMS is a specific type.

• DBMS may not support relationships between tables like RDBMS does.
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Q4. Opps concept in java
Ans. 
Oops concept in Java refers to Object-Oriented Programming principles like Inheritance, Encapsulation, Polymorphism, and Abstraction.
• Inheritance allows a class to inherit properties and behavior from another class.

• Encapsulation involves bundling data and methods that operate on the data into a single unit.

• Polymorphism allows objects to be treated as instances of their parent class.

• Abstraction hides the implementation d...read more
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Q5. Sorting algorithms in any language
Ans. 
Sorting algorithms are used to arrange elements in a specific order in an array.
• Common sorting algorithms include Bubble Sort, Selection Sort, Insertion Sort, Merge Sort, Quick Sort, and Heap Sort.

• Each algorithm has its own time complexity and best/worst case scenarios.

• For example, Merge Sort has a time complexity of O(n log n) and is efficient for large datasets.
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You will be given a dataset and a questionnaire to be solved over it

Q1. Explain confidance interval
Ans. 
Confidence interval is a range of values that is likely to contain the true population parameter with a certain level of confidence.
• Confidence interval is used to estimate the population parameter based on a sample statistic.

• It is calculated by taking the sample mean and adding or subtracting the margin of error.

• The level of confidence is typically set at 95% or 99%.

• For example, a 95% confidence interval for the averag...read more
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Q2. Explain logistic regression
Ans. 
Logistic regression is a statistical method used to analyze and model the relationship between a binary dependent variable and one or more independent variables.
• It is used to predict the probability of a binary outcome (0 or 1).

• It uses a sigmoid function to map the input values to the output probability.

• It is commonly used in machine learning for classification problems.

• Example: predicting whether a customer will buy a...read more
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Q3. Use of confusion matrix
Ans. 
Confusion matrix is a table used to evaluate the performance of a classification model.
• It helps in calculating various metrics like accuracy, precision, recall, F1 score, etc.

• It compares the predicted values with the actual values to identify true positives, true negatives, false positives, and false negatives.

• It is commonly used in machine learning and data science to evaluate the performance of classification models.

• ...read more
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Q4. Explain academic projects
Ans. 
Academic projects are assignments given to students to apply their theoretical knowledge in practical scenarios.
• Academic projects are designed to help students gain hands-on experience in their field of study.

• They require students to apply their theoretical knowledge to solve real-world problems.

• Examples of academic projects include building a website, designing a software application, conducting a research study, or c...read more
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Q1. What do you know about crif
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Q2. What do you want to learn here
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It was campus through internship

Q1. So it was through college so they did not ask me more
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Q2. Tell me about self Why investment banking
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