AI project lifecycle explained by an analogy- two examples

 A. 

Here’s an analogy using a science fair project to explain the AI project cycle :

1. Problem Scoping → Choosing a Science Fair Project Topic

Before starting a science project, you first decide what problem you want to solve. For example, "How can we make plants grow faster?"

2. Data Acquisition → Collecting Materials & Information

You gather what you need—seeds, soil, water, and information on plant growth. In AI, this step is like collecting data from various sources.

3. Data Exploration → Observing and Preparing the Data

Before planting, you check if your soil is good, your seeds are healthy, and if anything needs to be adjusted. In AI, this is where you clean and analyze data to make sure it’s useful.

4. Modelling → Conducting the Experiment

You plant seeds in different conditions (e.g., more sunlight, less water) and observe the growth. In AI, this is like training different models to see which one works best.

5. Evaluation → Checking the Results

After a few weeks, you measure which plants grew the fastest and analyze what worked. In AI, this step ensures the model performs well and meets expectations.

6. Deployment → Presenting at the Science Fair

Once you're confident in your results, you prepare a display and explain your findings. In AI, deployment means using the trained model in real-world applications.

B.

Here’s an analogy using planning a road trip:

1. Problem Scoping → Deciding the Destination

You and your friends decide to go on a road trip but need to figure out where to go, how long it will take, and what challenges you might face.

2. Data Acquisition → Gathering Information

You check maps, research routes, look at weather forecasts, and note gas stations, food stops, and hotels along the way.

3. Data Exploration → Analyzing Routes

You compare different routes—some might be shorter but have bad roads, while others take longer but are safer. You also check for traffic patterns.

4. Modelling → Choosing the Best Route

Based on your analysis, you pick a route that balances speed, safety, and fuel efficiency. You might also test-drive parts of the route beforehand.

5. Evaluation → Adjusting Plans if Needed

During the trip, you monitor real-time traffic and weather. If there’s a roadblock or a storm, you change the route accordingly.

6. Deployment → Completing the Trip Successfully

You reach your destination safely and on time, using all the planning and adjustments made along the way.