Cybersecurity Certificate

Security of informational assets has become a keenly debated issue for organizations. Effective information security management demands a clear understanding of technical as well as socio-organizational aspects. The purpose of this course is to prepare students to recognize the threats and vulnerabilities present in current information systems and how to plan for such risks. The course covers a broad range of topics including data classification, cryptography, network and application security, risk management, threat and vulnerability analysis, computer forensics, and policies and architecture designs. Students will have the opportunity to try real security and attack tools to understand how they work and how they might be used and counteracted.

Modern technologies have created a myriad of ways that data can be stored and communicated – and hidden. Digital forensics is the science of finding those data after the fact. This course presents an overview of the principles and practices of digital investigation and prepares students to conduct a cyber forensics investigation in an organized and systematic way. The course allows students to develop skills in collecting, seizing and analyzing suspect devices, creating forensics images, recover deleted data from various file systems and damaged media, apply digital forensics techniques to e-mail and other electronic communications and describe incident and intrusion response approaches among other topics.

Ethical hacking or penetration testing is the act of breaking into a system with the permission and legal consent of the organization or individual who owns and operates the system, with the purpose of identifying vulnerabilities to strengthening the organization's security. This course introduces students to the principles and techniques of the cybersecurity practice known as penetration testing and covers various tools and methods commonly used to compromise and control access to information systems. As part of this course, students will conduct hands-on penetration tests in a controlled lab environment, discover how system vulnerabilities can be exploited and learn how to avoid such problems in order to better secure organizational data and systems.

Cloud computing services (whereby distributed resources are rented, rather than owned) are being adopted across a variety of organizations yet many security challenges exist. This course introduces students to various cloud computing architectures and delivery models followed by a review of the security and privacy issues related to various types of cloud computing environments. The course covers aspects related to cloud security design, implementation, architecture, operations, controls, and compliance with regulatory frameworks for both cloud platforms & infrastructure security and cloud application security.

Protecting organizational assets against increased numbers of cybersecurity threats is of critical importance in all modern organizations. Having a cybersecurity plan and a governance structure in place for dealing with cybersecurity risks is a more successful strategy than recovering organizational systems after a cyberattack has occurred. This courses introduces students to risk management approaches for identifying, analyzing and responding to cybersecurity risks, governance mechanisms, human resource security and business continuity. This course provides students with necessary skills required to formulate and implement a cybersecurity plan.

Data mining is the process of discovering patterns and associations in large data sets. It supports decision making by detecting patterns, devising rules, identifying new decision alternatives and making predictions. This course provides an overview of leading data mining methods and their applications to real-world problems. It is designed to provide students with the skills to conduct data mining and statistical analysis for dealing with analytical tasks such as prediction, classification, decision trees and clustering. Students will use available software to conduct various data mining analyses and understand the application of a wide range of modern techniques to specific managerial and analytical situations, and on model interpretation.

More and more organizations are collecting large amounts of data, much of it unstructured. Big data technologies can be used to store, process and analyze large amounts of data using a distributed environment. This course introduces students to the world of big data and associated technologies. The focus of the course is Apache Hadoop, which is an open source software project that enables, distributed processing of large data sets across clusters of commodity servers. The objective of this course is to provide students a foundation for understanding big data technologies and Hadoop in particular. Topics include Hadoop system architecture, Hadoop Distributed File System (HDFS), MapReduce programming model and design patterns and technologies surrounding Hadoop ecosystem such as Pig, Hive and Oozie. The course will also introduce big data science concepts and NoSQL database technologies.