AI Project Cycle
Name: Your Name
Grade: 9
School: Your School Name
Tool Used: Suno AI
What is AI?
AI stands for Artificial Intelligence.
It means making computers think and act like humans.
AI helps in solving real-world problems smartly.
Why Do We Need an AI Project Cycle?
It gives a step-by-step method to build AI projects.
Helps organize our work better and smarter.
Ensures the project works correctly and solves the real problem.
1. Problem Scoping
We understand the problem we want to solve.
Think about: What is the goal of the project?
Example: Predict student exam performance.
2. Data Acquisition
We collect the data needed for the project.
This data could be from surveys, websites, or school records.
Example: Marks, attendance, homework completion.
3. Data Exploration
We clean and analyze the data.
Remove incorrect values and check for missing data.
Use graphs and charts to see patterns.
4. Model Building
We train the computer using the data we collected.
The computer learns from the data and makes predictions.
We can use tools like Suno AI to build the model.
Conclusion
AI Project Cycle has 4 main stages:
Problem Scoping
1 ️
1️⃣
Data Acquisition
2️⃣
Data Exploration
3 ️
3️⃣
Model Building
4️⃣
These help us build better AI projects.
Tools & References
AI Tool Used: Suno AI
Presentation created for school project.
Based on school AI textbook and project guidelines.

Colorful_AI_Project_Cycle_Presentation.pptx

  • 1.
    AI Project Cycle Name:Your Name Grade: 9 School: Your School Name Tool Used: Suno AI
  • 2.
    What is AI? AIstands for Artificial Intelligence. It means making computers think and act like humans. AI helps in solving real-world problems smartly.
  • 3.
    Why Do WeNeed an AI Project Cycle? It gives a step-by-step method to build AI projects. Helps organize our work better and smarter. Ensures the project works correctly and solves the real problem.
  • 4.
    1. Problem Scoping Weunderstand the problem we want to solve. Think about: What is the goal of the project? Example: Predict student exam performance.
  • 5.
    2. Data Acquisition Wecollect the data needed for the project. This data could be from surveys, websites, or school records. Example: Marks, attendance, homework completion.
  • 6.
    3. Data Exploration Weclean and analyze the data. Remove incorrect values and check for missing data. Use graphs and charts to see patterns.
  • 7.
    4. Model Building Wetrain the computer using the data we collected. The computer learns from the data and makes predictions. We can use tools like Suno AI to build the model.
  • 8.
    Conclusion AI Project Cyclehas 4 main stages: Problem Scoping 1 ️ 1️⃣ Data Acquisition 2️⃣ Data Exploration 3 ️ 3️⃣ Model Building 4️⃣ These help us build better AI projects.
  • 9.
    Tools & References AITool Used: Suno AI Presentation created for school project. Based on school AI textbook and project guidelines.