QUESTION BANK – CLASS 10 ARTIFICIAL INTELLIGENCE
CHAPTER 3: AI PROJECT CYCLE
One (01) Mark Questions
1. Name all the stages of an AI Project cycle.
Answer: Problem Scoping, Data Acquisition, Data Exploration, Modeling, Evaluation
2. What are sustainable development goals?
Answer: The Sustainable Development Goals (SDGs), also known as the Global Goals, were adopted by all United Nations Member States in 2015 as a universal call to action to end poverty, protect the planet and ensure that all people enjoy peace and prosperity.
OR
The Sustainable Development Goals (SDGs) or Global Goals are a collection of 17 interlinked goals designed to be a “blueprint to achieve a better and more sustainable future for all” so that the future generations may live in peace and prosperity.
3. Name the 4Ws of problem canvases under the problem scoping stage of the AI Project Cycle.
Answer: a. Who, b. what c. where d. why
4. What is Testing Dataset?
Answer: The dataset provided to the model ML. algorithm after training the algorithm
5. Mention the types of learning approaches for AI modeling.
Answer: Supervised, unsupervised and re-enforcement
6. What is the objective of evaluation stage?
Answer: It is to evaluate whether the ML algorithm is able to predict with high accuracy or not before deployment.
7. Fill in the blank:
The analogy of an Artificial Neural Network can be made with ____________ ?
Answer: Parallel Processing
8. Which of the following is not an authentic source for data acquisition?
a. Sensors b. Surveys c. Web Scraping d. System Hacking
Answer: (d) System Hacking
9. Which type of graphical representation suits best for continuous type of data like monthly exam scores of a student?
Answer: Linear graph
10. Fill in the blank: Neural Network is a mesh of multiple _______.
Answer: Hidden Layers / Layers
Two (02) Mark Questions
1. What are the two different approaches for AI modelling? Define them.
Answer: There are two approaches for AI Modelling; Rule Based and Learning Based.
The Rule based approach generates pre-defined outputs based on certain rules programmed by humans. Whereas, machine learning approach has its own rules based on the output and data used to train the models.
OR
Rule Based Approach Refers to the AI modelling where the relationship or patterns in data are defined by the developer. The machine follows the rules or instructions mentioned by the developer, and performs its task accordingly. Whereas in Learning based approach, the relationship or patterns in data are not defined by the developer. In this approach, random data is fed to the machine and it is left to the machine to figure out patterns and trends out of it
2. What is a problem statement template and what is its significance?
Answer: The problem statement template gives a clear idea about the basic framework required to achieve the goal. It is the 4Ws canvas which segregates; what is the problem, where does it arise, who is affected, why is it a problem? It takes us straight to the goal.
3. Explain any two SDGs in detail.
Answer:
(i) No Poverty: This is Goal 1 and strives to End poverty in all its forms everywhere globally by 2030. The goal has a total of seven targets to be achieved.
(ii) Quality Education: This is Goal 4 which aspires to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all. It has 10 targets to achieve.
* (Any two goals can be defined)
4. Mention the precautions to be taken while acquiring data for developing an AI Project.
Answer: It should be from an authentic source, and accurate. Look for redundant and irrelevant data parameters that does not take part in prediction.
5. What do you mean by Data Features?
Answer: The type of data to collect, It should be relevant data.
6. Write the names for missing stages in the given AI project cycle:
Answer: Problem scoping, Evaluation
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle
7. Draw the icons of the following SDGs : (i) Gender Equality (ii) Clean water and sanitation
Answer:
8. Draw the graphical representation of Classification AI model. Explain in brief.
Answer: Classification: The classification Model works on the labelled data. For example, we have 3 coins of different denomination which are labelled according to their weight then the model would look for the labelled features for predicting the output. This model works on discrete dataset which means the data need not be continuous.
OR
In classification, data is categorized under different labels according to some parameters given in input and then the labels are predicted for the data.
