Application of ML&Data Analysis In Electrical Engineering

A partner programme between Build_it and ELEESA-KNUST.

You have a dataset from a machine that keeps failing and a maintenance team that wants to know when to intervene. By the end of this programme you can answer that question with evidence.

Three hours, one real problem, worked start to finish. We take sensor readings from an industrial motor and go through the full path: loading and cleaning the data in Google Colab, choosing the right chart to actually see what is happening, building features out of what you already know from your electrical engineering courses, training a model, and then the uncomfortable part where a model that is [X]% accurate turns out to be useless because failures are rare.

You will use AI tools throughout, and you will learn to check their work. The skill here is not prompting. It is reading generated code, spotting the column it hallucinated, and knowing when the answer is wrong before you hand it to someone.

For students comfortable with Python basics. No prior machine learning required.