NPTEL Data Science Using Python – Week 1 : Assignment 1 Answers
- What is Data Science?
- Performing mathematical operations on data.
- Extracting meaningful information from data.
- Studying computer hardware systems.
- A branch of philosophy focused on data ethics.
2. Which of the following is NOT a motivation for Data Science?
- Amazon’s personalized recommendation system.
- Targeted advertising.
- Voice assistants like Google Voice, Siri, and Cortana.
- Speeding up internet connections.
3. Data Science is an interdisciplinary field that combines:
- Statistics, Biology, and Chemistry.
- Computer Science, domain expertise, and Philosophy.
- Statistics, Computer Science, and domain expertise.
- Mathematics, Physics, and domain expertise.
4. What is the primary goal of the data collection process?
- Storing data in cloud environments.
- Gathering data such as text, video, and audio.
- Processing data using machine learning algorithms.
- Creating data visualizations.
5. Which skill is essential for describing data?
- Web development.
- Cybersecurity.
- Statistics.
- Network engineering.
6. Which one of the following statements is true?
- Algorithmic modeling focuses more on prediction rather than understanding data.
- Statistical modeling exclusively uses machine learning algorithms.
- Algorithmic modeling cannot work with high-dimensional data.
- Statistical modeling is only used in finance and healthcare.
7. Which Python library is used for creating visualizations?
- Django.
- Flask.
- Matplotlib.
- TensorFlow.
8. What is the primary focus of data modeling?
- Creating physical models of data centers.
- Understanding relationships between variables and predicting outcomes.
- Designing database schemas.
- Building computer networks for data storage.
9. What is the primary goal of Artificial Intelligence (AI)?
- Creating systems that require constant human intervention.
- Mimicking human intelligence and functioning independently.
- Focusing solely on data storage and retrieval.
- Replacing all human tasks with robots.
10. Which of the following is NOT a task that constitutes AI?
- Problem solving.
- Data modeling.
- Decision making.
- Communication perception and actuation.
11. What distinguishes Machine Learning from traditional software programming?
- Machine Learning cannot make predictions.
- Machine Learning is not based on algorithms.
- Machine Learning algorithms can learn from data and improve over time.
- Machine Learning requires human intervention for learning.
12. What is a fundamental task of AI in problem-solving?
- Using large amounts of data to make decisions.
- Solving problems by searching through possibilities without needing data modeling.
- Relying solely on human input for solutions.
- Ignoring efficiency and logic in solving problems.
13. How does Data Science primarily differ from AI?
- Data Science does not involve algorithms.
- AI focuses on simulating human intelligence, while Data Science extracts insights from data for decision-making.
- Data Science aims to replace human decision-making entirely.
- AI uses data, while Data Science does not.
14. Which of the following areas is NOT directly involved in Data Science?
- Statistical analysis.
- Machine Learning.
- Autonomous vehicle engineering.
- Extracting insights from structured and unstructured data.
15. What is the significance of Machine Learning in Data Science?
- It is irrelevant to Data Science.
- It is the only aspect that matters in Data Science.
- It plays a pivotal role but is just one component of Data Science.
- It replaces the need for any statistical analysis.
