I don't think that the professors uploaded any sort of resource for everyone to use, but I can make some personal suggestions:

There's the obvious 'brute force' approach of just removing some of the data points to smooth out the curve a bit, but that is probably going to be your worst option in terms of time consumption.

With Matlab, you have a number of digital filtering options. You can use the fast Fourier transform and then inverse Fourier transform to filter out frequency peaks of noise. You could also use a Butterworth filter to filter out high frequency noise (oftentimes digital signals will have noise around 50 or 60 Hz due to AC electromagnetic interference from devices powered through wall outlets and such).

If you aren't confident with designing a digital filter, then you could probably just use the Matlab 'smooth' command, or for the final curve that you put in the document, you could even do a piecewise curve-fit for each part just to get them looking nice and piece them all together (obviously, you would still use your actual measured data to determine all the brass properties you need, this would just be for looks for the 'client').