Anyway, if you know python, try Pytorch Lightning Flash. It is simple to use and the tasks they have as part of it will give you a sense of what kinds of things ML does.
https://github.com/tensorflow/models
https://cv.gluon.ai/model_zoo/index.html
If there are no pre-trained models, you could take a look at fast.ai courses:
https://course18.fast.ai/ml.html (for Machine Learning (ML))
https://www.fast.ai (for others "DL" (Deep Learning))
This courses is targeted towards programmers, and they dive right into the code to use ML (train models and use them) with Jupyter notebooks. They also have a book whose notebooks are here: https://github.com/fastai/fastbook
If you have some maths background (high-school, or first year university), check out Stanford's CS229 with Andrew Ng:
https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXSh...
I think it's better than the Coursera version because he uses the board (whiteboard in 2018, blackboard in 2008-ish version)
What is the expected outcome from processing the data?