AI Project Cycle Class 10 Questions and Answers

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Teachers and Examiners (CBSESkillEduction) collaborated to create the AI Project Cycle Class 10 Questions and Answers. All the important QA are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class X.

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AI Project Cycle Class 10 Questions and Answers

ai project cycle class 10 questions and answers

1. What stages of an AI project are there?
Answer – There are five different stages of AI Project.
Problem Scoping >> Data Acquisition >> Data Exploration >> Modelling >> Evaluation

2. What is problem Scoping?
Answer – The process through which student designers “figure out” the problem they need to solve is called problem scoping. It is the procedure used to identify the issue.

You establish the objective for your AI project by identifying the issue you hope to address. When problem scoping, we consider several factors that have an impact on the issue we’re trying to address to make the situation more evident.

AI Project Cycle Class 10 Questions and Answers

3. How you can figure out the data using problem scoping?
Answer –

a. You need to acquire data which will become the base of your project.
b. Collect data from various reliable and authentic sources
c. After exploring the patterns, you can decide upon the type of model you would build to achieve the goal.
d. You can test the selected models and figure out which is the most efficient one.
e. The most efficient model is now the base of your AI project and you can develop your algorithm around it
f. Once the modelling is complete, you now need to test your model on some newly fetched data. The results will help you in evaluating your model and improving it.

AI Project Cycle Class 10 Questions and Answers

4. What is Sustainable Development?

Answer – When all renewable resources are utilized properly, the variety of life on earth is conserved, and environmental harm is kept to a minimum for the benefit of future generations, this is considered sustainable development.

According to the Bruntland Commission Report from 1987, sustainable development refers to “development that satisfies present demands without compromising the ability of future generations to meet their own needs.”

AI Project Cycle Class 10 Questions and Answers

5. What are the goals of sustainable development?
Answer – There are 17 sustainable development goals announced by the United nations, aim to achieve these goals by the end of 2030 –
a. No Poverty
b. Zero Hunger
c. Good Health and Well-being
d. Quality Education
e. Gender Equality
f. Clean Water and Sanitation
g. Affordable and Clean Energy
h. Decent Work and Economic Growth
i. Industry, Innovation and Infrastructure
j. Reduced Inequality
k. Sustainable Cities and Communities
l. Responsible Consumption and Production
m. Climate Action
n. Life Below Water
o. Life on Land
p. Peace and Justice Strong Institutions
q. Partnerships to achieve the Goal

6. What is 4Ws Problem Canvas?
Answer – Who, What, Where, and Why are the 4Ws of problem scoping. These Ws aid in more accurate and effective problem identification and comprehension.
a. who : who is facing for problem who are the stakeholders of problem .
b. what: what is refer to a asking question .
c. where : where is refer to asking about the place where the person was going.
d. why: why is refer to a asking about the person like why are you asking question .

AI Project Cycle Class 10 Questions and Answers

7. Who are the stakeholders?
Answer – Stakeholders are people who are either actively involved in the project or who have interests that the project’s results might influence. Project managers, project sponsors, executives, clients, or users are typically included in this group.

9. What do you mean by Problem Statement Template?
Answer – An stakeholders can define and describe a problem by writing a summarize report called a problem statement. Its objective is to offer a comprehensive plan of action to address the issue and include suggestions for how those responsible can stop it from happening again in the future.

10. What is data Acquisition?
Answer – The process of gathering correct and trustworthy data to work with is known as data acquisition. The second stage of the project cycle is data acquisition, and for successful decision making, we must make sure the data is gathered from genuine and trustworthy sources.

AI Project Cycle Class 10 Questions and Answers

11. What is the difference between Training Data & Testing Data?
Answer – The datasets are divided into two groups in machine learning. The first subset, referred to as the training data, is a section of our actual dataset that is used to train a machine learning model. Second subset, referred to testing data, Once your machine learning model is built, you need unseen data to test your model. This data is called testing data.

Note – Training data use 80% of the whole data and testing data use 20%.

12. What is data features?
Answer – Data features refer to the type of data you want to collect.

AI Project Cycle Class 10 Questions and Answers

13. What are the various ways to collect data?
Answer – Various ways to collect the data is –
a. Surveys
b. Web Scraping
c. Sensors
d. Cameras
e. Observations
f. Application Program Interface (API)

AI Project Cycle Class 10 Questions and Answers

14. What is data exploration?
Answer – Data exploration is the process of displaying and detecting unique patterns and trends in data using tools and procedures. Data visualization and other complex statistical techniques can be used to do this.

15. What is data modelling?
Answer – Data modelling is the process of developing a visual representation of an entire information system or certain components of it. for example the development, training, and application of machine learning algorithms that simulate logical decision-making based on accessible facts are known as AI modelling.

16. Types of AI Modelling?
Answer – AI Models are classified into two type –
a. Learning Based
b. Rule Based

AI Project Cycle Class 10 Questions and Answers

17. What is Rule Based Approach?
Answer – When the developer sets the rules. The machine executes its duty in accordance with the rules or instructions specified by the developer.
A rule-based artificial intelligence (AI) system is one that aims to develop artificial intelligence (AI) by using a model that is exclusively based on predetermined rules.

18. What is Learning Based Approach?
Answer – AI modelling where the computer learns on its own. The AI model is trained on the data provided to it under the Learning Based technique, and after that, it is able to create a model that is flexible to the change in data.

AI Project Cycle Class 10 Questions and Answers

19. What are the different type of Learning based approach?
Answer – The learning based approach can be divided into three types –

a. Supervised Learning – In order for a computer to learn from data, it must have external supervision. This is known as supervised learning. We use the labelled dataset to train the supervised learning models. Supervised machine learning is a method for addressing two major issues: regression and classification.

b. Unsupervised Learning – This term refers to a sort of machine learning in which the machine can learn from the data on its own without any external supervision. The unlabelled dataset can be used to train the unsupervised models. These are employed in order to address the Association and Clustering issues.

c. Reinforcement Learning – Reinforcement learning is a learning process where an agent interacts with its environment by taking actions and learns through feedback. The agent receives feedback in the form of rewards; for example, he receives a positive reward for each good activity and a negative reward for each bad action. The agent is not under any oversight. Reinforcement learning makes use of the Q-Learning algorithm.

AI Project Cycle Class 10 Questions and Answers

20. Who many type of Supervised Learning models in AI?
Answer – There are two types of Supervised Learning model –
a. Classification – When the data is labeled-based categorized. For instance, under the grading system, students are categorized based on the grades they receive in relation to their exam marks.

b. Regression – Such models work on continuous data. For example, if you wish to predict your next salary,
then you would put in the data of your previous salary, any increments, etc., and would train the model.

AI Project Cycle Class 10 Questions and Answers

21. How many type of Unsupervised Learning model in AI?
Answer – There are two type of Unsupervised learning models in AI –
a. Clustering – refers to the unsupervised learning technique that can cluster the unknown data according to patterns or trends found in it. The developer may already be aware of the patterns noticed, or it may even generate some original patterns as a result.

b. Dimensionality Reduction – If you have a large number of features, it could be beneficial to minimise them using an unsupervised step before moving on to supervised steps. Numerous unsupervised learning techniques include a transform technique that can be used to lessen the dimensionality.

AI Project Cycle Class 10 Questions and Answers

22. What is Evaluation?
Answer – By feeding the test dataset into the model and comparing the outputs to the actual results, evaluation is the process of determining the dependability of any AI model. Depending on the kind of model and its intended use, many evaluation procedures may be used.

23. Give a brief introduction to the Turing test in AI?
Answer – One of the widely used intelligence tests in artificial intelligence is the Turing test. In the year 1950, Alan Turing developed the Turing test. A machine’s ability to think like a human is being tested in this experiment. This test states that a computer can only be considered intelligent if it can imitate human behaviour in specific situations.

In this test, there are three participants: a computer, a human responder, and a human interrogator. The interrogator’s job is to determine which response is coming from the machine based on the questions and responses.

24. What is overfitting? How can it be overcome in Machine Learning?
Answer – Overfitting in the model happens when the machine learning algorithm tries to include all of the data points and, as a result, includes noise as well. This overfitting problem causes the algorithm to display low bias but large output variance. One of the biggest problems with machine learning is overfitting.

AI Project Cycle Class 10 Questions and Answers

25. What is Expert System?
Answer – An expert system in artificial intelligence is a computer programme that mimics the capacity for judgement of a human expert. Expert systems are created to reason through knowledge bases that are primarily represented as if-then rules rather than through traditional procedural code.

26. What is the use of computer vision in AI?
Answer – Computers may be taught to understand and extract data from the visual environment, such as photographs, using an area of artificial intelligence called computer vision. Thus, computer vision makes use of AI technology to resolve challenging issues like image processing and object detection.

27. What is confusion matrix in ai?
Answer – An N x N matrix called a confusion matrix is used to assess the effectiveness of a classification model, where N is the total number of target classes. In the matrix, the actual goal values are contrasted with those that the machine learning model anticipated.

AI Project Cycle Class 10 Questions and Answers

28. What is F1 score in ai?
Answer – When data are unbalanced, such as when the number of cases belonging to one class greatly outnumbers those found in the other class, the F1 score is a popular performance metric for classification and is frequently selected over, for example, accuracy.

29. Why shouldn’t the training data be used for evaluation?

Answer – This is so that our model will always predict the right label for any point in the training set because it will just remember the entire training set.

AI Project Cycle Class 10 Questions and Answers

30. Give an example of a circumstance where a false positive would come at a high cost.

Answer – Let’s have a look at a model that can determine whether a message is spam or not. People would not read the letter if the model consistently predicted that it was spam, which could lead to the eventual loss of crucial information. Here, a false positive condition (predicting that a message is spam when it is not) would be expensive.

31. What is a confusion matrix? What is it used for?

Answer – The comparison between the prediction and reality’s outcomes is stored in the confusion matrix. We can determine variables like recall, precision, and F1 score, which are used to assess an AI model’s performance, from the confusion matrix.

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