TCS Lead Data Scientist Interview Questions and Answers

*****, arjumpudi satyanarayana

Q1. What is the python language
Ans. 
Python is a high-level programming language known for its simplicity and readability.
• Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.

• It emphasizes code readability and uses indentation for block delimiters.

• Python has a large standard library and a vibrant community of developers.

• Example: print('Hello, World!')

• Example: import pandas as pd
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Q2. What is the code problems
Ans. 
Code problems refer to issues or errors in the code that need to be identified and fixed.
• Code problems can include syntax errors, logical errors, or performance issues.

• Examples of code problems include missing semicolons, incorrect variable assignments, or inefficient algorithms.

• Identifying and resolving code problems is a key skill for data scientists to ensure accurate and efficient data analysis.
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Q3. What is the python code
Ans. 
Python code is a programming language used for data analysis, machine learning, and scientific computing.
• Python code is written in a text editor or an integrated development environment (IDE)

• Python code is executed using a Python interpreter

• Python code can be used for data manipulation, visualization, and modeling
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Q4. What is the project
Ans. 
The project is a machine learning model to predict customer churn for a telecommunications company.
• Developing predictive models using machine learning algorithms

• Analyzing customer data to identify patterns and trends

• Evaluating model performance and making recommendations for reducing customer churn
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Q5. What is the lnderssip
Ans. 
The question seems to be incomplete or misspelled.
• It is possible that the interviewer made a mistake while asking the question.

• Ask for clarification or context to provide a relevant answer.
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Q1. Tell me about yourself?
Ans. 
I am a data scientist with a background in statistics and machine learning, passionate about solving complex problems using data-driven approaches.
• Background in statistics and machine learning

• Experience in solving complex problems using data-driven approaches

• Passionate about leveraging data to drive insights and decision-making
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Q2. Describe in detail about one of my main project.
Ans. 
Developed a predictive model for customer churn in a telecom company.
• Collected and cleaned customer data including usage patterns and demographics.

• Used machine learning algorithms such as logistic regression and random forest to build the model.

• Evaluated model performance using metrics like accuracy, precision, and recall.

• Implemented the model into the company's CRM system for real-time predictions.
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Q3. Few questions related to my projects.
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Q1. Questions on Basics python(Since i am fresher)
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Q1. Which GenAI projects I have worked on
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Q2. What is the context window in LLMs
Ans. 
Context window in LLMs refers to the number of surrounding words considered when predicting the next word in a sequence.
• Context window helps LLMs capture dependencies between words in a sentence.

• A larger context window allows the model to consider more context but may lead to increased computational complexity.

• For example, in a context window of 2, the model considers 2 words before and 2 words after the target word fo
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Q3. What is top_k parameter
Ans. 
top_k parameter is used to specify the number of top elements to be returned in a result set.
• top_k parameter is commonly used in machine learning algorithms to limit the number of predictions or recommendations.

• For example, in recommendation systems, setting top_k=5 will return the top 5 recommended items for a user.

• In natural language processing tasks, top_k can be used to limit the number of possible next words in a
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Q4. What are regex patterns in python
Ans. 
Regex patterns in Python are sequences of characters that define a search pattern.
• Regex patterns are used for pattern matching and searching in strings.

• They are created using the 're' module in Python.

• Examples of regex patterns include searching for email addresses, phone numbers, or specific words in a text.
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Q5. What are iterators and tuples
Ans. 
Iterators are objects that allow iteration over a sequence of elements. Tuples are immutable sequences of elements.
• Iterators are used to loop through elements in a collection, like lists or dictionaries

• Tuples are similar to lists but are immutable, meaning their elements cannot be changed

• Example of iterator: for item in list: print(item)

• Example of tuple: my_tuple = (1, 2, 3)
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Q6. Do I have REST API experience
Ans. 
Yes, I have experience working with REST APIs in various projects.
• Developed RESTful APIs using Python Flask framework

• Consumed REST APIs in data analysis projects using requests library

• Used Postman for testing and debugging REST APIs
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Q1. Deep questions about Machine learning, Deep learning, Generative AI, the working of transformers etc.
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Q1. Deep questions about Machine learning and deep learning with projects done. This was a client round.
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Q1. Salary discussion, project discussion, why change? Why Wipro
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Q1. Tell me about your self?
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Q2. What is maths and stats
Ans. 
Maths and stats refer to the study of mathematical concepts and statistical methods for analyzing data.
• Maths involves the study of numbers, quantities, shapes, and patterns.

• Stats involves collecting, analyzing, interpreting, and presenting data.

• Maths is used to solve equations, calculate probabilities, and model real-world phenomena.

• Stats is used to make informed decisions, draw conclusions, and test hypotheses.

• Both ma...read more
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Confusion matrix what are your job rolls explain me Gradient boosting algorithm?

Expect technical questions as well as moderate level coding questions

Q1. Data science and MLOps concepts
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Q1. Behavioral and managerial rounds
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A="bala",b="Babu";
Print=A+b
O/p:
balababu

Python is a computer programming language use to build up software and websites designed by Rossum appear in 20 Feb 1991
1.Numpy is a python libraries working with arrays.
2.pandas is used to read the data sets.
3.matplotlib libraries for visualisation.
4.mission learning is divided into two parts.
*Supervised learning
*Unsupervised learning
5.deep learning is used to create artificial neurons.
6.advance excel is used for graphs and calculate the whole members at same time lot of useful things that have.
7mysql is mainly used for store the data.

Python, numpy, pandas, mission learning, deep learning, basic statistics, advance excel, MySQL

Python, numpy, pandas, mission learning, deep learning, basic statistics, advance excel, MySQL

Q1. Why we use mission learning Mission learning used for analysis the data's and we can able to predict and we add some additional algorithm it's mainly used for prediction and AI.
Ans. 
Mission learning is used for data analysis and prediction with additional algorithms for AI.
• Mission learning is a subset of machine learning that focuses on predicting outcomes based on data analysis.

• It involves using algorithms to learn patterns and make predictions based on new data.

• Examples include image recognition, natural language processing, and recommendation systems.
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Q2. Deep learning uses: Deep learning Mainly used for creating artificial neurons in the neural network. Deep learning is very aid about the mission how to work and artificial intelligence helps also
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Q3. Statistics: Statistics is used for mathamatics operation and it helps to prediction. Example: We started to calculate how many persons live in between 20to25 age. That time statistics is very help to reduc...read more
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I don't know idea about group discussion