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AI Variant Data Science Intern Interview Questions and Answers

Updated 15 Sep 2024

AI Variant Data Science Intern Interview Experiences

3 interviews found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Walk-in and was interviewed in Mar 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Data Science , machine learning, python

Round 2 - Coding Test 

Coding on python, mysql, r

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed before Jun 2022. There were 2 interview rounds.

Round 1 - Assignment 

I have completed assignments. I done all methods of algorithms and data models with good accuracy

Round 2 - Direct internship position 

(1 Question)

  • Q1. Based on assignment score they will arrange it by groups.

Interview Preparation Tips

Topics to prepare for AI Variant Data Science Intern interview:
  • Machine Learning
  • Data Science
  • Data Analysis
  • Python
  • MySQL
  • Tableau
  • Powerbi
  • Excel

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I applied via Company Website and was interviewed before Oct 2021. There were 2 interview rounds.

Round 1 - Coding Test 

Coding questions related to basic python, and Loops, oops concept.

Round 2 - HR 

(2 Questions)

  • Q1. Tell me about yourself. What are your strengths?
  • Ans. 

    I am a data science intern with strong analytical skills and a passion for problem-solving.

    • Strong analytical skills

    • Passion for problem-solving

    • Experience in data analysis and visualization

    • Proficient in programming languages like Python and R

    • Ability to work with large datasets

    • Excellent communication and teamwork skills

  • Answered by AI
  • Q2. What is your weakness?
  • Ans. 

    My weakness is that I tend to be overly critical of my own work.

    • I often spend too much time reviewing and revising my work to ensure it is perfect.

    • I have a tendency to doubt my abilities and seek validation from others.

    • I sometimes struggle with prioritizing tasks and can become overwhelmed with multiple projects.

    • I am working on improving my self-confidence and learning to trust my own judgment.

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - The interview is intermediate. The interviewer asked no high-level questions.

Interview questions from similar companies

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Campus Placement and was interviewed in Nov 2024. There were 3 interview rounds.

Round 1 - Aptitude Test 

There were verbal, non verbal, reasoning , English and maths questions

Round 2 - Technical 

(2 Questions)

  • Q1. Tell me about your project.
  • Ans. 

    I worked on a project analyzing customer behavior using machine learning algorithms.

    • Used Python for data preprocessing and analysis

    • Implemented machine learning models such as decision trees and logistic regression

    • Performed feature engineering to improve model performance

  • Answered by AI
  • Q2. What programming knowledge you have ?
  • Ans. 

    Proficient in Python, R, and SQL with experience in data manipulation, visualization, and machine learning algorithms.

    • Proficient in Python for data analysis and machine learning tasks

    • Experience with R for statistical analysis and visualization

    • Knowledge of SQL for querying databases and extracting data

    • Familiarity with libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn

  • Answered by AI
Round 3 - HR 

(2 Questions)

  • Q1. Where do you stay ?
  • Ans. 

    I currently stay in an apartment in downtown area.

    • I stay in an apartment in downtown area

    • My current residence is in a city

    • I live close to my workplace

  • Answered by AI
  • Q2. Tell me about you
  • Ans. 

    I am a data science enthusiast with a strong background in statistics and machine learning.

    • Background in statistics and machine learning

    • Passionate about data science

    • Experience with data analysis tools like Python and R

  • Answered by AI
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
-
Result
-

I applied via Campus Placement

Round 1 - Technical 

(1 Question)

  • Q1. ML and deep learning questions
Round 2 - Interview 

(2 Questions)

  • Q1. Projects discussion
  • Q2. Chatgpt architecture
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

Basic DSA questions will be asked Leetcode Easy to medium

Round 2 - Technical 

(2 Questions)

  • Q1. BERT vs LSTM and their speed
  • Ans. 

    BERT is faster than LSTM due to its transformer architecture and parallel processing capabilities.

    • BERT utilizes transformer architecture which allows for parallel processing of words in a sentence, making it faster than LSTM which processes words sequentially.

    • BERT has been shown to outperform LSTM in various natural language processing tasks due to its ability to capture long-range dependencies more effectively.

    • For exa...

  • Answered by AI
  • Q2. What is multinomial Naive Bayes theorem
  • Ans. 

    Multinomial Naive Bayes is a classification algorithm based on Bayes' theorem with the assumption of independence between features.

    • It is commonly used in text classification tasks, such as spam detection or sentiment analysis.

    • It is suitable for features that represent counts or frequencies, like word counts in text data.

    • It calculates the probability of each class given the input features and selects the class with the

  • Answered by AI

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via campus placement at Chennai Mathematical Institute, Chennai and was interviewed in Dec 2023. There was 1 interview round.

Round 1 - One-on-one 

(3 Questions)

  • Q1. What are Large Language Models?
  • Ans. 

    Large Language Models are advanced AI models that can generate human-like text based on input data.

    • Large Language Models use deep learning techniques to understand and generate text.

    • Examples include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).

    • They are trained on vast amounts of text data to improve their language generation capabilities.

  • Answered by AI
  • Q2. Do you know about RAGs?
  • Ans. 

    RAGs stands for Red, Amber, Green. It is a project management tool used to visually indicate the status of tasks or projects.

    • RAGs is commonly used in project management to quickly communicate the status of tasks or projects.

    • Red typically indicates tasks or projects that are behind schedule or at risk.

    • Amber signifies tasks or projects that are on track but may require attention.

    • Green represents tasks or projects that ar...

  • Answered by AI
  • Q3. Which is the best clustering algorithm?
  • Ans. 

    There is no one-size-fits-all answer as the best clustering algorithm depends on the specific dataset and goals.

    • The best clustering algorithm depends on the dataset characteristics such as size, dimensionality, and noise level.

    • K-means is popular for its simplicity and efficiency, but may not perform well on non-linear data.

    • DBSCAN is good for clusters of varying shapes and sizes, but may struggle with high-dimensional d...

  • Answered by AI

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Campus Placement and was interviewed in Jun 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Some basic aptitude questions were asked , but had to be solved in 20 minutes

Round 2 - Coding Test 

Medium level 2 leet code questions were asked and i cleared both

Round 1 - Technical 

(1 Question)

  • Q1. Basic python and machine learning questions
Round 2 - HR 

(1 Question)

  • Q1. Salary expectation and working location related questions and why you want to join wipro

Interview Preparation Tips

Interview preparation tips for other job seekers - Focus on basic python and machine learning
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I was interviewed in Dec 2023.

Round 1 - Aptitude Test 

English, number system, grammar

Round 2 - Coding Test 

Python , data science, machine learning

Round 3 - Assignment 

Python machine learning, natural language precossing

Round 4 - HR 

(4 Questions)

  • Q1. Python , Data Science, SQL
  • Q2. What is python basics, libraries
  • Ans. 

    Python basics include syntax, data types, and control structures. Libraries like NumPy, Pandas, and Matplotlib enhance data analysis and visualization.

    • Python basics cover syntax, variables, data types, and control structures.

    • NumPy is a library for numerical computing, providing powerful array operations.

    • Pandas is a library for data manipulation and analysis, offering data structures like DataFrames.

    • Matplotlib is a libr...

  • Answered by AI
  • Q3. Data science algorithms , and theory
  • Q4. Sql querys, cluases
Round 5 - Group Discussion 

Indian environment, village, college days

Round 6 - HR 

(1 Question)

  • Q1. Python, data science

AI Variant Interview FAQs

How many rounds are there in AI Variant Data Science Intern interview?
AI Variant interview process usually has 2-3 rounds. The most common rounds in the AI Variant interview process are Resume Shortlist, Coding Test and HR.

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AI Variant Data Science Intern Salary
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₹1 L/yr - ₹7 L/yr
10% less than the average Data Science Intern Salary in India
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AI Variant Data Science Intern Reviews and Ratings

based on 29 reviews

4.4/5

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4.2

Skill development

4.2

Work-Life balance

3.1

Salary & Benefits

3.7

Job Security

4.2

Company culture

3.5

Promotions/Appraisal

4.1

Work Satisfaction

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