Information Technology Online Master's Degree Program

Students will be using FTK Imager, Magnet Encrypted Disk Detector, OS Forensics Volatility Workbench, Kali Linux, Reg Ripper, Network Miner, and Wireshark to develop a foundation framework for the practice of Digital investigations, including technical and managerial issues.

Understanding risk and identifying the threats organizations face are essential skills for today's information security professionals. In this course that introduces students to the graduate degree program, students learn to compute impact scores for vulnerabilities, classify data, and use Champlain College Online's virtual environment to explore how to use IOCs (Indicators of Compromise).

In this course students learn to differentiate relational and non-relational databases, and to design a database to an organization's requirements. Preparing raw data for import into a database, using queries to manipulate data, and developing reports to meet stakeholder needs, and database integrity and security are also covered.

Students will gain an understanding and respect for emerging technology by exploring current trends in security and examining topics such as artificial intelligence, machine learning, blockchain and behavior analytics. Students will analyze the science behind these technologies as well as the ethical and privacy concerns and implications that may hinder their widespread adoption.

This course is designed to introduce a systematic process for planning, organizing and controlling projects. The course will present a practical methodology for completing projects more quickly with fewer problems. Student work will consist of readings, research, class special-topic presentations, group activities, a project management journal, and participation in a real world IT business project. Students will be encouraged to apply project-management techniques to solve existing real-world technology-related business problems.

In SDEV-520, Software Engineering, students learn about the field of software engineering, including project management methodologies applied to the field of Software Development, economic factors that affect development decisions and product life cycle, requirement gathering and assessment, and modelling languages. Disruptive technologies and methodologies and their impact on this field are also covered in this course.

In this course students demonstrate mastery of the information technology concepts and skills learned and acquired through the Master of Science in Information Technology degree program via successful completion of a Capstone project. Students are required to complete a reflection assignment to produce additional insight.

Students learn to create and use scripts to access, acquire, prepare, and transform data, including structured and semi-structured data, and to define and detect patterns in unstructured data to demonstrate how real world problems can be answered with data.

Scripting languages like Python can help security professionals extend available tools but also create new tools to address specific needs. Extensive labs in this course have students attacking MD5 hashes, web scraping, parsing security logs and breaking a cipher.

Students will develop the ability to write basic python scripts (WIngIDE) to help in digital investigations. Students will also interpret scripts written in other languages, like EnCase Enscript or Perl or Microsoft Powershell or UNIX Shell Script.

The world is increasingly characterized by diversity and an integrated economy. Balancing the business opportunities and risks associated with dynamic and uncertain global changes is critical to effective leadership in this global economy. Leaders must learn how to integrate their understanding of culture, ethics, economic and policial issues into their decision making and strategy development.

Throughout history, technology provided opportunities for innovation, resulting in changes in business and society at a global scale. These technologies often disrupted business policies and processes, impacting jobs and organizational structures. Students examine how technological innovation is experienced in society and viewed over time and into the future by business people, philosophers, and sociologists. Students explore the question, How do we imagine that business, society and our place within will be affected as technology continues to advance?

Students learn organization analysis from a holistic perspective. Financial reports and financial ratios are the basis for traditional organizational analysis and builds from that foundation into the analysis of customer, supplier and employee metrics. Focus is on the Balanced Scorecard and other holistic approaches.

Students use a framework to explore the dynamics of human interaction within and between organizations. Throughout the course, they will use a perspective that a key function of management is to negotiate for resources and use that perspective to develop collaborative relationships with employees, vendors, suppliers, and interested communities.

Students learn to create and use scripts to access, acquire, prepare, and transform data, including structured and semi-structured data, and to define and detect patterns in unstructured data to demonstrate how real world problems can be answered with data.

In this course students learn about deep learning, machine learning, and artificial intelligence, and compare supervised and unsupervised learning. Machine learning workflows and the challenges associated with machine learning, such as bias and heteroscedasticity, are considered. Students evaluate models, and examine uses for machine learning and artificial intelligence. Natural Language Processing is also addressed.

In this course students learn about different types of data and methods of visualization so they can select appropriate visualization techniques, and prepare and visualize data for specific audience(s). The role of human perception and its impact on the design and communication of graphical representations of information is also examined.

In this course students learn about data types and how to perform pre-processing activities including cleaning, integration, reduction, and transformation. Use of appropriate techniques to analyze and model data, such as classification, decision trees, association rules, and clustering, and the causes and methods of detecting outliers are also covered. Students propose additional applications for data mining based on current trends/research.

Students will be using FTK Imager, Magnet Encrypted Disk Detector, OS Forensics Volatility Workbench, Kali Linux, Reg Ripper, Network Miner, and Wireshark to develop a foundation framework for the practice of Digital investigations, including technical and managerial issues.

Hands-on labs and assignments using Kali Linux, Metasploitable, Nessus and Armitage build on previously acquired knowledge of threat and vulnerability classification in this course that allows students to use the knowledge of a vulnerability to perform threat analysis. Vulnerability and patch management processes are also addressed.

Students will use tools such as The Sleuth Kit and Volatility to conduct forensic analysis of PC & server operating systems and software running on those systems, while gaining a knowledge set of forensic relevant information about operating systems, including those used in mobile devices. Finally, students will look at the challenges of virtualization, including those that come with the growth of Cloud systems.

In this class, students use tools like nfdump, Snort and Wireshark for network forensic analysis in the context of the role of an incident response team.

In SDEV-530, students will use software modelling techniques and formal representation, including Unified Modelling Language (UML), to represent and design software systems.

In this course students study the specificity of managing software development projects, covering all areas identified by the Project Management Institute in the PMBoK? Software Extension. The application of these concepts to alternative forms of project management are also covered in this course.

In this course, students study Agile project management methodologies, in the context of software development, as a way of achieving Software Engineering quality goals. Students will learn what projects lend themselves to an agile approach, and how the agile approach relates to traditional project management, while learning the tools and techniques of Agile.

In this course, students will learn how to plan and implement software testing using quality assurance frameworks.