# 30+ Important QnA Data Acquisition AI Class 10

In this article, I am going to discuss some important QnA Data Acquisition AI class 10. Data Acquisition is the second stage of AI project cycle. So let’s start this article Important QnA Data Acquisition AI Class 10!

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## Important QnA Data Acquisition AI Class 10

As usual and CBSE sample paper pattern, let’s begin the article with Objective Type Questions for this article Important QnA Data Acquisition AI Class 10. As usual, I will discuss objective and subjective type questions.

## Objective type questions (OTQs)

This section consists of MCQs, fill in the blanks and True/False. So here we go!

1. The ___________ is second stage of AI project cycle. (Ans. Data Acquisition)
2. Data acquisition refers to collect data through various activities. (True/False)
3. Which of the can be a piece of information or facts and statistics collected together for reference or analysis?
1. Data
2. Problem statement
3. Feedback
4. All of these
4. To predict the output you must train the data for the AI project. (True/False)
5. In data acquisition the data which is provided as input is called __________. (Ans. Training Data)
6. The prediction data is known as _________ data in Data Acquisition. (Ans. Testing)
7. We can provide any data for the prediction to get a better result. (True/False)
8. The type of data being collected in data acquisition is known as ____________. (Ans. Data Features)
9. Which of the following is not a method to collect data?
1. Surveys
2. Web Scrapping
3. Sensors
4. Archives
10. Which of the following is one of the government open source for collecting data?
1. www.ayushmanbharat.org
2. www.india.gov.in
3. www.bharatdata.in
4. www.india.com
11. The data which contain whole numbers categorized into which of the following categories?
1. Continuous numeric data
2. non-continuous numeric data
3. Discrete numeric data
4. uncountable numeric data
12. The data which can be in the form of any value within a range is considered as which of the following categories of data?
1. Continuous numeric data
2. non-continuous numeric data
3. Discrete numeric data
4. uncountable numeric data
13. Data has been organized according to some predefined rules, ideas or unorganized. (True/False)
14. The data which has predefined structure and organized in predefined manner is called _________________ data. (Ans. structured)
15. The types of data that do not have any predefined structure are known as unstructured data. (Ans. unstructured)
16. The combination of structured and unstructured data is known as _________ data. (Ans. semi-structured)
17. The data which is time order defining the sequence according to some event time is known as ___________ data. (Ans. time-stamped)
18. Which of the following data helps in forming an accurate of actions over time?
1. structured data
2. unstructured data
3. semi-structured
4. time-stamped
19. Machine data refers to the data collected from systems or programs like called details, emails data etc. (True/False)
20. The data from user behaviour, activities or actions is known as _________ data. (Ans. machine)
21. The data which contains both location and time information is known __________ data. (Ans. spatiotemporal)
22. The data which is available freely for everyone to use which is not restricted through copyrights, patents, control etc is known as ______ data. (Ans. open)
23. The data which is available as soon as an event takes place is known as __________ data. (Ans. real-time)
24. Which of the following not one of the Vs of big data?
1. volume
2. velocity
3. variety
4. version
25. The _____________ refers to is more concerned with maintaining and managing the metadata rather than the database itself. (Ans. data curation)

In the next section of important QnA Data Acquisition AI Class 10, We are going to discuss some subjective type questions.

## Subjective Type Questions (STQs)

In this section of important QnA Data Acquisition AI Class 10, you will get 2 and 4 marks questions. So here we go!

1. What do you understand by data acquisition?
• Data acquisition is the second step of AI project cycle.
• It refers to collecting data from various sources and through various activities to train the model.
• The data which is collected as input can be considered training data and the prediction data provided by the system or project is known as testing data.
2. Explain the training data and testing data with an example.
• The existing data or previous data collected through various activities or sources is known as training data and prediction data is known as testing data.
• For example, If someone wants to predict the salary of an employee based on previously drawn salaries into the machine, the previous salary is training data and prediction salary data is known as testing data.
3. Justify the sentence – “For any AI project to be efficient, the training data should be authentic and relevant to the problem statement scoped.”
• For AI project efficiency the data needs to be relevant and authentic.
• If it is not relevant and authentic then the testing data may go wrong or produce irrelevant predictions.
• For example, while processing data for a cricket match for net run rate prediction, the testing data should be provided for batting, not bowling. If the bowler’s data will be processed as testing data then the net run rate will be predicted in the wrong direction.
• Hence, for any AI project to be efficient, the training data should be authentic and relevant to the problem statement scoped.
4. What do you mean by data features?
• Data features refer to the type of data that needs to be collected for an AI model or project.
• For example, if we consider an example of a cricket match then runs scored by an individual batsman, runs scored in particular overs, wickets fall, wickets runs conceded, wicket particulars etc. can be considered as data features.
5. Mention the ways to collect data.
• The following ways are very common to collect data:
• Surveys
• Web Scrapping
• Sensors
• Cameras
• Observations
• API
• Call or SMS or Email
• Feedback
6. What are some concerns that need to be taken care of while collecting data?
• The data should be authentic
• The data should be accurate
• Collect the data from reliable sources
• Data should be open source not someone’s intellectual property
7. Mention two websites from where we get open-source data.

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