AI Project Cycle: Class 10 Notes, Worksheet & Answers

By Anjeev Kr Singh – Computer Science Educator
Published on : December 2, 2025 | Updated on : December 2, 2025

AI Project Cycle: Class 10 Notes, Worksheet & Answers

Artificial Intelligence Notes

AI Project Cycle

• To develop an AI Project, the AI Project Cycle provides us with an appropriate framework which can lead us towards the goal. 
• The AI project cycle is the cyclical process followed to complete an AI project.
• The AI Project Cycle mainly has 6 stages:

1. Problem Scoping:

Under the problem scoping, we 

• Set the goal for your AI project by stating the problem which you wish to solve with it.
• Look at various parameters which affect the problem we wish to solve so that the picture becomes clearer.

2. Data Acquisition

• You need to acquire data which will become the base of our project as it will help you understand what the parameters that are related to problem scoping are. 
• You go for data acquisition by collecting data from various reliable and authentic sources. 

3. Data Exploration

• Since the data you collect would be in large quantities, you can try to give it a visual image of different types of representations like graphs, databases, flow charts, maps, etc. 
• This makes it easier for you to interpret the patterns which your acquired data follows. 

4. Modelling

• After exploring the patterns, you can decide upon the type of model you would build to achieve the goal. For this, you can research online and select various models which give a suitable output. 
• You can test the selected models and figure out which is the most efficient one. 
• The most efficient model is now the base of your AI project and you can develop your algorithm around it. 

5. Evaluation

• 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. 

6. Deployment

• Finally, after evaluation, the deployment stage is crucial for ensuring the successful integration and operation of AI solutions in real-world environments, enabling them to deliver value and impact to users and stakeholders.

WORKSHEET: AI PROJECT CYCLE

A. Multiple Choice Questions (10)

1. The AI Project Cycle consists of how many main stages?
   a) 4 b) 5 c) 6 d) 7
2. Setting the goal for your AI project is part of which stage?
   a) Data Acquisition b) Problem Scoping c) Modelling d) Evaluation
3. The process of collecting data from various reliable sources is called:
   a) Data Exploration b) Deployment c) Data Acquisition d) Evaluation
4. Visualising collected data using graphs and charts belongs to:
   a) Modelling b) Problem Scoping c) Data Exploration d) Deployment
5. Selecting the most efficient model happens during:
   a) Modelling b) Evaluation c) Problem Scoping d) Deployment
6. Testing the model on new data is done in which stage?
   a) Data Acquisition b) Modelling c) Evaluation d) Deployment
7. Integrating the final AI model into real-world applications is known as:
   a) Modelling b) Deployment c) Evaluation d) Problem Scoping
8. Identifying the various parameters affecting the problem occurs during:
   a) Data Acquisition b) Problem Scoping c) Deployment d) Evaluation
9. The stage where you understand patterns in the acquired data is:
   a) Data Exploration b) Modelling c) Evaluation d) Deployment
10. Creating an algorithm around the selected model is part of:
    a) Data Exploration b) Evaluation c) Modelling d) Data Acquisition

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B. Fill in the Blanks (5)

1. The AI Project Cycle is a __________ process.
2. Under data acquisition, data is collected from __________ sources.
3. Data exploration helps in identifying __________ in the data.
4. After selecting the best model, we develop an __________ around it.
5. Deployment ensures successful integration of the model into __________ environments.

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C. Short Answer Questions (5)

1. What is the purpose of problem scoping?
2. Why is data acquisition important in an AI project?
3. What is meant by data exploration?
4. What happens during the evaluation stage?
5. Why is deployment an important part of the AI Project Cycle?

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📘 ANSWER KEY (With Questions and Answers)

A. MCQ Answer Key

1. Q: The AI Project Cycle consists of how many main stages?
   A: c) 6
2. Q: Setting the goal for your AI project is part of which stage?
   A: b) Problem Scoping
3. Q: The process of collecting data from various reliable sources is called:
   A: c) Data Acquisition
4. Q: Visualising collected data using graphs and charts belongs to:
   A: c) Data Exploration
5. Q: Selecting the most efficient model happens during:
   A: a) Modelling
6. Q: Testing the model on new data is done in which stage?
   A: c) Evaluation
7. Q: Integrating the final AI model into real-world applications is known as:
   A: b) Deployment
8. Q: Identifying the various parameters affecting the problem occurs during:
   A: b) Problem Scoping
9. Q: The stage where you understand patterns in the acquired data is:
   A: a) Data Exploration
10. Q: Creating an algorithm around the selected model is part of:
    A: c) Modelling

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B. Fill in the Blanks – Answer Key

1. Q: The AI Project Cycle is a __________ process.
   A: cyclical
2. Q: Under data acquisition, data is collected from __________ sources.
   A: reliable and authentic
3. Q: Data exploration helps in identifying __________ in the data.
   A: patterns
4. Q: After selecting the best model, we develop an __________ around it.
   A: algorithm
5. Q: Deployment ensures successful integration of the model into __________ environments.
   A: real-world

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C. Short Answer Key

1. Q: What is the purpose of problem scoping?
   A: To identify the problem clearly and set the goal of the AI project by understanding all parameters related to the problem.
2. Q: Why is data acquisition important in an AI project?
   A: Because it provides the raw data needed to analyse patterns, train models, and understand the factors affecting the problem.
3. Q: What is meant by data exploration?
   A: It is the process of visually analysing collected data through graphs, charts, and other tools to understand patterns and trends.
4. Q: What happens during the evaluation stage?
   A: The model is tested on new data to check its accuracy, performance, and reliability.
5. Q: Why is deployment an important part of the AI Project Cycle?
   A: Because it ensures that the developed model is implemented in real-world applications where it can provide actual value to users.

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