Machine Learning for Cybersecurity offered by The University of Chicago
- Private University
- 217 acre campus
- Estd. 1890
Machine Learning for Cybersecurity at UChicago Overview
Machine Learning for Cybersecurity
at UChicago
Evolve your cyber risk strategy with advanced training in machine learning for cybersecurity from the center for data and computing
Duration | 5 weeks |
Start from | Start Now |
Total fee | ₹2.50 Lakh |
Mode of learning | Online |
Official Website | Go to Website |
Course Level | UG Certificate |
Machine Learning for Cybersecurity at UChicago Highlights
Machine Learning for Cybersecurity
at UChicago
- Earn a certificate from the University of Chicago
- Learn from industry experts
Machine Learning for Cybersecurity at UChicago Course details
Machine Learning for Cybersecurity
at UChicago
Skills you will learn
Who should do this course?
- For individuals who want to enhance their knowledge & skills in the field
What are the course deliverables?
- Understand basic concepts for statistical modeling, including principles for model selection for supervised and unsupervised learning tasks in the context of cybersecurity
- Select the most appropriate models for various cybersecurity scenarios, such as malware classification, botnet detection, and intrusion detection
- Detect and defend against adversarial attacks on machine learning models in cybersecurity settings at both training and test times
- Identify and understand means of navigating legal and ethical challenges that emerge from gathering data about human subjects and using it to build machine-learning models
More about this course
- In this four-day certificate course, you will develop the technical skills necessary to learn how to deploy data-driven prevention strategies using machine learning and other innovative solutions
- Faculty will teach cutting-edge cybersecurity methods using real-world case studies and datasets, building both fundamental and practical knowledge
- Information security managers, engineers, and professionals whose role includes working in applied computer security or cybersecurity are encouraged to enroll. Prior experience with machine learning is not required
Machine Learning for Cybersecurity at UChicago Curriculum
Machine Learning for Cybersecurity
at UChicago
Foundations of Machine Learning for Security
Data-Driven Network and Computer Security
Machine Learning in the Presence of Adversaries
Ethics, Fairness, Responsibility, and Transparency in Data-Driven Cybersecurity
Secure Machine Learning Development & Deployment
Machine Learning for Cybersecurity at UChicago Faculty details
Machine Learning for Cybersecurity
at UChicago
Yuxin Chen
Yuxin Chen is an assistant professor at the Department of Computer Science at the University of Chicago. Previously, he was a postdoctoral scholar in Computing and Mathematical Sciences at Caltech, hosted by Prof. Yisong Yue.
Nick Feamster
Nick Feamster is the Neubauer Professor in the Department of Computer Science and the College, and faculty director of the Center for Data and Computing.
Blase Ur
Blase Ur researches computer security, privacy and human-computer interaction. His focus is on helping users make better security and privacy decisions, and improving user experience within complex computer systems.
Machine Learning for Cybersecurity at UChicago Entry Requirements
Machine Learning for Cybersecurity
at UChicago
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at UChicago
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Machine Learning for Cybersecurity at UChicago Contact Information
Machine Learning for Cybersecurity
at UChicago
Address
Edward H. Levi Hall 5801 South Ellis Avenue Chicago, Illinois 60637 USA
Chicago ( Illinois)
Phone
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