This course provides an accessible introduction to foundational data science techniques and algorithms using cybersecurity examples and use cases. Data science is rapidly becoming an integral part of the network security industry. Although widespread applications of data science in network security are relatively recent, data science has roots going back decades. Due to its depth and technical complexity, data science is often considered to be indistinguishable from magic. This course is intended to demystify data science and show how specific data science techniques can be applied to network data.
The afternoon session answers important questions including:
- What is data science, anyways? (short version)
- I don’t have enough data. What do I do? Or worse, I have too much data! What do I do?
- Too many algorithms, which one do I choose (if any)?
- I managed to choose an algorithm; now how do I make it work?
- I (finally) got a model, did I do it right?
Intended Audience: Practitioners, managers, and/or executives who are curious to strengthen their understanding of data science concepts and techniques in an accessible, introductory setting. Experience with applied math, statistics, and/or coding is beneficial, but not required.
