TVS Credit Data Analyst Interview Questions and Answers

Q1. It was more related to my projects
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Q2. Asked questions on PCA,KNN and Elbow method .
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Q1. Asked SVM and Logistic regression, their applications and real life uses
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Q2. Matrix formation of a knockout Tournament
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Asked questions of finance and aptitude

Q1. What is machine learning?
Ans. 
Machine learning is a branch of artificial intelligence that involves developing algorithms and models that enable computers to learn from and make predictions or decisions based on data.
• Machine learning is a subset of artificial intelligence that focuses on developing algorithms that can learn from and make predictions or decisions based on data.

• It involves training models on large datasets to recognize patterns and m...read more
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Q2. What do you know about SQL?
Ans. 
SQL is a programming language used for managing and manipulating relational databases.
• SQL stands for Structured Query Language

• It is used to retrieve and manipulate data in relational databases

• Common SQL commands include SELECT, INSERT, UPDATE, DELETE

• SQL can be used to create tables, indexes, and views

• Examples of SQL databases include MySQL, PostgreSQL, Oracle
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Q3. What you know about software Development?
Ans. 
Software development involves creating, designing, testing, and maintaining software applications.
• Software development includes coding, testing, debugging, and documenting software applications.

• Developers use programming languages like Java, Python, C++, etc. to write code.

• Agile and Waterfall are common software development methodologies.

• Version control systems like Git are used to manage code changes.

• Software developm...read more
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Q1. What are the algorithms you know in machine learning and their details ?
Ans. 
Various machine learning algorithms with brief details
• Supervised Learning: Linear Regression, Logistic Regression, Support Vector Machines (SVM), Decision Trees, Random Forest

• Unsupervised Learning: K-means Clustering, Hierarchical Clustering, Principal Component Analysis (PCA)

• Reinforcement Learning: Q-Learning, Deep Q-Networks (DQN)

• Neural Networks: Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), L
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Q2. Python questions
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Apptitude test conducted where there are 60 question in 60 min

Python, Verbal , Apptitude

Last one is interview round

Q1. Tell me about yourself?
Ans. 
I am a highly skilled and experienced Business Analyst with a strong background in data analysis and problem-solving.
• Experienced Business Analyst with expertise in data analysis and problem-solving

• Strong analytical skills and ability to interpret complex data

• Proficient in using various tools and software for data analysis

• Excellent communication and presentation skills

• Proven track record of successfully identifying busi
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Q2. Tell me project you have worked
Ans. 
I worked on a project to improve inventory management for a retail company.
• Implemented a new inventory tracking system to streamline processes

• Conducted data analysis to identify trends and optimize stock levels

• Collaborated with cross-functional teams to gather requirements and ensure smooth implementation
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