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Sabudh Foundation Data Science Intern Interview Questions and Answers

Updated 27 Sep 2024

Sabudh Foundation Data Science Intern Interview Experiences

3 interviews found

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

I applied via Company Website and was interviewed in Dec 2023. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Complexity of binary search
  • Ans. 

    Binary search is a logarithmic time complexity algorithm used to search for a target value in a sorted array.

    • Binary search divides the array in half at each step, reducing the search space by half each time.

    • Time complexity of binary search is O(log n) where n is the number of elements in the array.

    • Example: Searching for value 5 in array [1, 3, 5, 7, 9] would take 2 steps in binary search.

  • Answered by AI
  • Q2. Some questions were from ml, ai

Skills evaluated in this interview

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

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

Round 1 - Aptitude Test 

Total 50 questions,some form time and work,logical reasoning,blood relationship,directions

Round 2 - reading question and answering 

(2 Questions)

  • Q1. Tell us about yourself
  • Ans. 

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

    • Completed coursework in data analysis, statistical modeling, and machine learning

    • Proficient in programming languages such as Python, R, and SQL

    • Experience with data visualization tools like Tableau and Power BI

    • Worked on projects involving predictive modeling and data mining

  • Answered by AI
  • Q2. Which color do you like and why ?
  • Ans. 

    I like the color blue because it reminds me of the ocean and brings a sense of calmness and tranquility.

    • Blue is associated with peace, tranquility, and relaxation

    • It is often used in interior design to create a calming atmosphere

    • Examples: blue sky, blue ocean, blue flowers

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - very good to start intern in virtual mode

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Interview experience
4
Good
Difficulty level
Easy
Process Duration
More than 8 weeks
Result
Selected Selected

I applied via Company Website and was interviewed in Nov 2022. 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 - Aptitude Test 

Aptiude Test is very easy it contains 50 questions

Round 3 - Technical 

(4 Questions)

  • Q1. In technical internview basic questions about machine learning and Mathematics
  • Q2. Linear and Logistic Regression
  • Q3. Bernoulli Distribution
  • Q4. Python build in data types
  • Ans. 

    Python has several built-in data types including numeric, sequence, mapping, and set types.

    • Numeric types include integers, floats, and complex numbers.

    • Sequence types include lists, tuples, and strings.

    • Mapping types include dictionaries.

    • Set types include sets and frozensets.

    • Each data type has its own set of methods and operations.

    • Examples: int(5), float(3.14), complex(2+3j), list([1,2,3]), tuple((1,2,3)), str('hello'), ...

  • Answered by AI

Skills evaluated in this interview

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

Sabudh Foundation Interview FAQs

How many rounds are there in Sabudh Foundation Data Science Intern interview?
Sabudh Foundation interview process usually has 2 rounds. The most common rounds in the Sabudh Foundation interview process are Aptitude Test, Technical and Resume Shortlist.
What are the top questions asked in Sabudh Foundation Data Science Intern interview?

Some of the top questions asked at the Sabudh Foundation Data Science Intern interview -

  1. Python build in data ty...read more
  2. Complexity of binary sea...read more
  3. In technical internview basic questions about machine learning and Mathemat...read more

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Sabudh Foundation Data Science Intern Interview Process

based on 3 interviews

Interview experience

4.3
  
Good
View more
Sabudh Foundation Data Science Intern Salary
based on 6 salaries
₹1 L/yr - ₹6 L/yr
24% less than the average Data Science Intern Salary in India
View more details

Sabudh Foundation Data Science Intern Reviews and Ratings

based on 7 reviews

4.6/5

Rating in categories

4.8

Skill development

4.8

Work-life balance

3.4

Salary

4.0

Job security

4.8

Company culture

4.0

Promotions

4.6

Work satisfaction

Explore 7 Reviews and Ratings
Data Science Intern
6 salaries
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₹1 L/yr - ₹6 L/yr

Data Scientist
4 salaries
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₹6 L/yr - ₹9 L/yr

Jr. Data Scientist
4 salaries
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₹8 L/yr - ₹12 L/yr

Intern
3 salaries
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₹1 L/yr - ₹5 L/yr

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3 salaries
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₹3.8 L/yr - ₹5 L/yr

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