The following write-up attempts to summarize the resources I’ve found helpful as a means to update my technical knowledge with all of the skills necessary to work and meaningfully contribute in the field of AI and Machine Learning. For context, I hold a B.Sc. in Computer Science with a focus in Computational Neuroscience and I’ve worked for many years as a Front-end / Full-Stack Web Developer, although I’ve always been strong at math.
For an excellent free introduction that covers just about everything you need to know about neural networks, deep learning, and transformer models in a relatively simplistic way. I was recommended the 3Blue1Brown video series on YouTube by Vlad, one of my co-workers during my AI internship at Bongard.ai:
'The Little Book of Deep Learning' is a free, phone-friendly intro to AI. Perfect for a focused learning break. https://fleuret.org/francois/lbdl.html
I personally opted for the Stanford Professional Certificate Program as a recommendation made by my mentors D & T. Although it was extremely difficult to tackle after being out of school for quite some time, I found the experience to be invaluable because it gave me the conceptual understanding and language to follow along with just almost any paper, tutorial, or discussion today.
I’ve written two articles; one about the pros and cons of the Artificial Intelligence Professional Program and one about XCS221: What I Wish I knew before I started.
The Pros and Cons of Stanford Online Learning Courses For AI and Machine Learning: The Stanford…