Syngenta Data Science Intern Interview Questions and Answers

Q1. Tell me about yourself
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Q2. What is an invoice?
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An invoice is a document issued by a seller to a buyer, detailing the products or services provided and the amount due.
• An invoice typically includes information such as the seller's contact information, the buyer's contact information, a description of the products or services provided, the quantity, the price, and the total amount due.

• Invoices are used in business transactions to request payment from the buyer for the...read more
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Q1. How did you ever feel like you were going to fail at something?
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45 mins, accounting concepts

Q1. What is equity, debenture
Ans. 
Equity represents ownership in a company, while debenture is a type of debt instrument issued by a company.
• Equity represents ownership in a company and gives shareholders voting rights and a share in profits.

• Debenture is a type of debt instrument issued by a company, typically with a fixed interest rate and maturity date.

• Equity holders are considered residual claimants, meaning they are paid after debenture holders in
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Q2. TDS, GST, GST rates, Bad debts
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Q1. Technical round is was there.
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Normal aptitude test with low to moderate level questions.

A topic is coined and we need to speak about it.

Basic Aptitude test Medium level

Technical topic related to IT Industry, 3 got shortlisted out of 8

Q1. Intro, CV, Workex based questions
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Q2. Situational question related to IT Industry problem
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Q1. What is data science
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Data science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
• Data science involves collecting, analyzing, and interpreting large amounts of data to solve complex problems.

• It combines statistics, machine learning, data visualization, and domain expertise to make data-driven decisions.

• Examples of data science applic...read more
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Q2. What are different ml algorithms
Ans. 
Machine learning algorithms are techniques used to enable machines to learn from data and make predictions or decisions without being explicitly programmed.
• Supervised learning algorithms: Decision Trees, Random Forest, Support Vector Machines

• Unsupervised learning algorithms: K-means Clustering, Hierarchical Clustering, Principal Component Analysis

• Reinforcement learning algorithms: Q-Learning, Deep Q-Networks

• Deep learni...read more
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