The AI Project Cycle is a step-by-step process used to develop an Artificial Intelligence solution. It helps students understand how real-life problems can be solved using AI in a systematic way. The AI Project Cycle consists of five main stages: Problem Scoping, Data Acquisition, Data Exploration, Modelling, and Evaluation.
AI Project Cycle Class 8 MCQs
1. The AI project cycle is a:
a) Linear process for developing AI projects.
b) Cyclical process guiding AI development from start to finish.
c) Random approach to building AI models.
d) One-time evaluation method for AI projects.
2. What is the primary goal of problem scoping in the AI project cycle?
a) To define the specific problem the AI will address.
b) To gather data for training the AI model.
c) To choose an AI algorithm for model building.
d) To evaluate the performance of the AI model.
3. The 4W Canvas (Who, What, When, Where) is a helpful tool for:
a) Selecting data visualization techniques.
b) Defining clear objectives in problem scoping.
c) Evaluating the accuracy of the AI model.
d) Implementing the chosen AI algorithm.
4. In the context of AI projects, data acquisition refers to:
a) The amount of data collected.
b) The format of the data (e.g., numbers, text).
c) How well the data relates to the problem being solved.
d) The source from which the data is collected.
5. Which of the following is NOT a benefit of data exploration in the AI project cycle?
a) Makes it difficult to identify patterns and trends in data.
b) Improves communication and understanding of data insights.
c) Simplifies the process of choosing an AI algorithm.
d) Reduces the time required for data exploration.
6. What is the main purpose of the modeling stage in the AI project cycle?
a) To refine the problem definition based on data analysis.
b) To build a computer program that can solve the identified problem.
c) To test the performance of the AI model in real-world situations.
d) To gather additional data if needed.
7. Which of the following statements about the AI project cycle is FALSE?
a) It helps ensure teams stay organized and focused on key tasks.
b) It promotes collaboration among different specialists working on the project.
c) It is a rigid, inflexible process that cannot be adapted to different situations.
d) It defines clear deliverables for each stage, guiding project progress.
8. Imagine you’re building an AI system to predict flight delays. During data acquisition, what type of data would be most relevant?
a) User reviews of airline companies.
b) Weather forecasts for different destinations.
c) Images of airplanes taking off and landing.
d) Historical data on flight delays and cancellations.
9. Which one of the following is an application of AI?
a. Remote controlled Drone
b. Self-Driving Car
c. Self-Service Kiosk
d. Self-Watering Plant System
10. What does NLP stand for in AI?
a. Neutral Learning Projection
b. Neuro-Linguistic Programming
c. Natural Language Processing
d. Neural Logic Presentation
11. Which of the following is not a domain of artificial intelligence?
a. Data Management System
b. Computer Vision
c. Natural Language Processing
d. Data Science
12. Which one of the following is the second stage of AI project cycle?
a. Data Exploration
b. Data Acquisition
c. Modelling
d. Problem Scoping
13. Which of the following comes under Problem Scoping?
a. System Mapping
b. 4Ws Canvas
c. Data Features
d. Web scraping
14. Which of the following is not valid for Data Acquisition?
a. Web scraping
b. Surveys
c. Sensors
d. Announcements
15. Which of the following is not a part of the 4Ws Problem Canvas?
a. Who?
b. Why?
c. What?
d. Which?
16. The stages of the AI project cycle are _.
a. Problem Scoping & Data Acquisition
b. Data Exploration & Modeling
c. Evaluation
d. All of the above
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