Since my last blog post about Ethical Hacking in my Masters in Cybersecurity courses, I’ve wrapped on 3 more courses. These were Machine Learning, Risk Management & System Hardening, and the latest Data Mining. The Data Mining and Machine Learning courses has a lot of parity, same instructor and covered similar areas.
It was really good to get into the machine learning aspect especially when combined with a Cybersecurity application, to learn how these methods are applied and then integrated into a platform that as a decision maker on what software to purchase when defending a network, you won’t just fall for the buzz words of “AI Enabled”. Having a core understanding of what machine learning is and how it is applied takes some of the mystique out the propaganda. I won’t say machine learning is necessarily an easy class of computer science, there is advanced statistical and mathematical theory at play, but most of the work of this is already done by people way smarter than us, and as a developer we can just take advantage of the APIs that leverage various models.
I’d like to get deeper into this topic at some point on my blog, but the fact of the matter is I’m rarely even able to find a few minutes to even post a short update like this one, and I have to start preparing for my summer class, Advanced Cryptography.