This course provides an accessible introduction to foundational data science concepts, terminology, and approaches 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 break the illusion and help attendees harness the true power of data science to defend networked systems.
The morning session will answer important questions, including:
- Are data science and machine learning truly different from artificial intelligence?
- Is this product really using machine learning or just faking it?
- I have a data science model, now what do I do?
- How can I tell timeseries and graph data apart?
- What makes “deep” learning different from other approaches?
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. There are no prerequisites for this course; however, an understanding of math, statistics, and coding is helpful.
