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Brave AI Lab Data Science Intern Interview Questions and Answers

Updated 25 Apr 2024

Brave AI Lab Data Science Intern Interview Experiences

1 interview found

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

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

Round 1 - Technical 

(2 Questions)

  • Q1. Computer Vision Question on detecting coins in an image
  • Q2. Easy-Medium level Python Question
Round 2 - Technical 

(1 Question)

  • Q1. Basic AI/ML questions & 1 Medium-Hard Python Question

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
-
Process Duration
-
Result
-
Round 1 - Group Discussion 

Time structure is a part of Environment that used as reference to measure and keep track . The structure of the time also a central . And overall the structure of time remains of the debate.

Round 2 - Technical 

(1 Question)

  • Q1. Data Science and Programming
Round 3 - Aptitude Test 

Mathematics and other questions

Interview Preparation Tips

Interview preparation tips for other job seekers - Data developer and programming
Interview experience
1
Bad
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Job Portal and was interviewed in Oct 2023. There were 4 interview rounds.

Round 1 - Coding Test 

Coding test is important

Round 2 - Coding Test 

Most important in coding test

Round 3 - Group Discussion 

Group discussion is share the projects many people one idea

Round 4 - HR 

(1 Question)

  • Q1. Last round in HR round in salary details joining in company
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Recruitment Consulltant and was interviewed in Aug 2023. There were 3 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Technical 

(1 Question)

  • Q1. About your project and experience
Round 3 - Coding Test 

Core Python questions were asked

Brave AI Lab Interview FAQs

How many rounds are there in Brave AI Lab Data Science Intern interview?
Brave AI Lab interview process usually has 2 rounds. The most common rounds in the Brave AI Lab interview process are Technical.
How to prepare for Brave AI Lab Data Science Intern interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Brave AI Lab. The most common topics and skills that interviewers at Brave AI Lab expect are Algorithm Development, Computer Vision, Data Science, Image Processing and Neural Networks.
What are the top questions asked in Brave AI Lab Data Science Intern interview?

Some of the top questions asked at the Brave AI Lab Data Science Intern interview -

  1. Computer Vision Question on detecting coins in an im...read more
  2. Basic AI/ML questions & 1 Medium-Hard Python Quest...read more
  3. Easy-Medium level Python Quest...read more

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