ZignaAI Jr. Data Scientist Interview Questions and Answers

This was good aptitude test computer based

Coding round share screen and code

Q1. Explains OOPs concept
Ans. 
OOPs (Object-Oriented Programming) is a programming paradigm based on the concept of objects, which can contain data and code.
• OOPs focuses on creating objects that interact with each other to solve complex problems.

• Key principles of OOPs include encapsulation, inheritance, polymorphism, and abstraction.

• Encapsulation involves bundling data and methods that operate on the data into a single unit (object).

• Inheritance allo...read more
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Q2. Explain SOLID principles
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SOLID principles are a set of five design principles in object-oriented programming to make software more maintainable, flexible, and scalable.
• Single Responsibility Principle (SRP) - A class should have only one reason to change.

• Open/Closed Principle (OCP) - Software entities should be open for extension but closed for modification.

• Liskov Substitution Principle (LSP) - Objects of a superclass should be replaceable with...read more
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Q1. What is precision and recall
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Precision and recall are evaluation metrics used in machine learning to measure the performance of a classification model.
• Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.

• Recall is the ratio of correctly predicted positive observations to the all observations in actual class.

• Precision is important when the cost of false positives is high, while recall is i...read more
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Q1. Evaluation metrics used in multiclass classification
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Evaluation metrics for multiclass classification
• Accuracy

• Precision

• Recall

• F1 Score

• Confusion Matrix
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Q2. Difffereence between append and extend
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Append adds a single element to a list while extend adds multiple elements.
• Append adds the element as it is to the end of the list.

• Extend takes an iterable and adds each element of the iterable to the end of the list.

• Append can be used to add a single element to a list.

• Extend can be used to add multiple elements to a list.

• Example: list1 = [1, 2, 3], list2 = [4, 5], list1.append(4) will result in [1, 2, 3, 4], list1.ext
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Q3. Sort a list and take out second minimum
Ans. 
Sort a list and extract the second minimum value.
• Sort the list in ascending order using the sort() method.

• Extract the second minimum value using indexing.

• Handle cases where the list has less than two elements.
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Q1. What are the different supervised models used
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Supervised models include linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks.
• Linear regression: used for predicting continuous outcomes

• Logistic regression: used for binary classification

• Decision trees: used for classification and regression tasks

• Random forests: ensemble method using multiple decision trees

• Support vector machines: used for classification ...read more
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Q2. Linear regression, logistic regression, decision tree
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Q1. What are the salary expectations
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Do well and contribute well

Do well and contribute well

Do well and contribute well

Q1. Why we choose this job
Ans. 
I am passionate about using data to solve complex problems and make meaningful insights.
• I have a strong background in statistics and data analysis

• I enjoy working with large datasets and finding patterns within them

• I am excited about the opportunity to work on real-world problems and make a positive impact
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Q2. What are your expectations
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I expect challenging projects, opportunities for growth, supportive team environment, and continuous learning.
• Challenging projects that allow me to apply my skills and knowledge

• Opportunities for growth and advancement within the company

• Supportive team environment where collaboration and knowledge sharing are encouraged

• Continuous learning through training, workshops, and mentorship programs
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Q1. Tell me about your self
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I am a data-driven individual with a strong background in statistics and machine learning.
• Graduated with a degree in Statistics

• Proficient in programming languages like Python and R

• Experience with data visualization tools like Tableau

• Completed projects involving predictive modeling and data analysis
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Q2. What are your salary expectations
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I am looking for a competitive salary based on my skills and experience.
• Research industry standards for Jr. Data Scientist salaries

• Consider my level of experience and education

• Factor in the cost of living in the area where the job is located
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Fibonacci series print

Sales dataset to predict future sales

Normal there is not advance requirment

Q1. Will you work will less amount package
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Q2. You wouldn't get any travel cost?
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Q3. What about machine learning
Ans. 
Machine learning is a branch of artificial intelligence that focuses on developing algorithms and models that can learn from and make predictions or decisions based on data.
• Machine learning involves training algorithms to learn patterns from data and make predictions or decisions.

• It can be supervised, unsupervised, or semi-supervised learning.

• Examples include recommendation systems, image recognition, and natural langu
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Q4. Tellm me about any cloud platform
Ans. 
A cloud platform is a service that allows users to store, manage, and process data remotely.
• Cloud platforms provide scalable and flexible storage solutions

• They offer various services such as computing power, databases, and analytics tools

• Examples include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform
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Q5. Telll me about pointer
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A pointer is a variable that stores the memory address of another variable.
• Pointers are used to access and manipulate memory directly.

• They are commonly used in programming languages like C and C++.

• Example: int *ptr; // declaring a pointer variable
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Q1. Introduction and overview of the projects
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Q1. Computer vision questions
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