ML Model development with Python

The level has eight lessons. The students will learn the concept of Data Science. Various data sets will be given to students. They will learn to display the data sets in Jupyter Notebooks; preparing the models and do the predictions. 

Case Study I: When It is going to rain?

Set up micro: bits and collect the data (Datalog) and keep the .csv files. Design the model and predict the weather (i.e., when it is going to rain?)

Data Collection and Model Deployment

Design to collect data with micro: bits. Create .CSV files and analyse the data. The students will also learn to develop the models and to build a web application to deploy the ML models.