Page 22 - CT_AI_Class-8

21 st
Century #Information Literacy
experiential learning activity Skills

Collect and record weather data over the course of one month to understand the process of data
collection and analysis. Track weather data such as temperature, humidity and wind speed over a one-
month period. Each day, record the following:
 Maximum temperature

 Minimum temperature

 Average temperature
Data can be gathered either by using a weather app or website or by manually observing and recording
the information in an Excel spreadsheet.

Model Development and Training

After completing data collection and data preparation, the next step in the AI project life cycle
is Model Development and Training. In this stage, an AI model is designed and built to solve the
problem identified earlier. The prepared data is then used to train the model so that it can learn
patterns, relationships and trends within the data.

An AI model works like the brain of the system. It analyses the input data, identifies meaningful

patterns and learns from examples. Once the learning process is complete, the model can use
this knowledge to make predictions, classify data or support decision-making.
This process is similar to how humans learn. For example, when students practice solving different

types of questions, they gradually understand patterns and improve their performance. In the
same way, an AI model learns from large amounts of data and improves over time.

For example,

Predicting Student Gadget Screen Time

Let us take the Gadget Screen Time example. The goal is to predict whether a student has high or
low screen time.
The AI model will learn using the following data:

Student Gadget Screen Sleep Outdoor Academic Screen
Type Time Hours Activity Score Time Level

Student 1 1 5 6 30 65 1

Student 2 3 2 9 60 80 0

Student 3 2 4 7 45 70 1
Student 4 3 1.5 8 90 85 0

20 Artificial Intelligence (CT & AI)-VIII