Cyber Data Science for DCO (closed : max capacity)

Instructor : Jacob Baxter | Capacity : 18 | Length : 6 Hours | Time : 0900 -1200 & 1300 - 1600

Instructor: Jacob Baxter

Background:

A Former Army Officer, Jacob is a technologist who has always followed his curiosity and interest in technology, having a core belief in its ability to make the world a better place. He has a background in Applied Mathematics and got into Cybersecurity as an Army Officer, working a defensive mission set on traditional large enterprise networks, while based in Augusta, GA. He’s been in the field now for about 6 years, and then has spent time doing a lot of research at DARPA and in the DOD on using programming, data science, and machine learning to try to help improve Cybersecurity. Presently he spends a majority of his time working on tough research questions as a Research Fellow in the United States Military Academy’s Cyber Research Center and trying to make cool tech at Orang Labs. He’s been a practicing Cyber Data Scientist for over 5 years, with experience utilizing Data Science for Cyber Problems in DOD DCO, at DARPA, and in his current roles. If he wasn’t working the 9 to 5, all of his friends know he’d be found on a side-street in Bali, speaking Indonesian with the local Ayam Goreng (fried chicken) or Sate cart, waiting for his next Ultimate Frisbee game to start.

Difficulty: Intermediate Description:

This workshop will teach the basics of performing Data Science and Machine Learning in Python for Cyber Security Applications. We’ll cover statistical, graph, unsupervised, and supervised approaches to analytics. Attendees will walk away with the ability to use Python to answer questions about Cyber Data, such as projecting and grouping similar IPs based on their network flows, predicting unlabeled admin accounts from account behavior, and visualizing these types of problems to help communicate to other analysts and stakeholders.

Required Materials: Laptops and Laptop Chargers

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