Hello everyone,

I got briefly involved with Virgilio a couple of years back while I was still early in my journey in deep learning and for more than one reason I got side tracked.

I am currently working at a mobile robotics startup as the lead software engineer, and for computer vision solutions (non-deep learning) that I need to use for our robots I am going back to studying math and stats and linear algebra.

I did remember that Virgilio had a guide containing a list of good resources to learn these topics so I gave the website a visit and it was truly heartwarming to see Virgilio is going strong.

Anyhow, I checked the calc 1 course from MIT and I did push through it a bit, and I'd like to think of myself as a mathematically inclined person, but with the workload I have and the mental drain that comes with that, it was very difficult for me to keep up with the content the way I wanted it to be done.

So here's an alternative course: Prof. Leonard's Calc 1. He explains it very well, he does not leave details, and granted it is not as deep of an understanding as the MIT course gives, I believe it is a completely reasonable baseline for calculus. I will attempt to update you guys on any good resources I might find for the rest of the topics as I get to them, but for now that is my suggestion. I think Prof Leonard's courses could be a worthwhile alternative to the MIT courses for those who are mostly interested in applications of calc (for any purpose, including deep learning).

Nonetheless, I leave the choice to the capable hands of those running Virgilio to decide whether they would like to include a less intensive, less in-depth, more applications-oriented approach the the preliminary topics or not.