CIT 381: Linux Technology (Fall "C" 2022) (G10)

This course is intended for students who want to learn about the Linux operating system and prepare to pass the Linux+ certification exam from CompTIA (Powered by LPI). It does not assume any prior knowledge of Linux and is geared toward those interested in systems administration as well as those who will use or develop programs for Linux systems. The course provides comprehensive coverage of topics related to Linux certification, including Linux distributions, installation, administration, X-Windows, cloud technologies, networking, and security.

CIT 110: Computer Operating Systems (Fall "C" 2022) (G13)

The Computer Operating Systems course prepares the student to acquire the necessary knowledge in managing and maintaining operating systems on personal computers of an entry-level IT professional. Student must also demonstrate competency in critical thinking during the decision-making process for computer deployment to meet expected client requirements as well customer service skills.


CIT 105: Programming Practice (Fall "C" 2022) (G13)

This course follows the Introduction to Computer Programming course (CIT102) and is dedicated to implementing the most common data structures (such as lists, stacks, files, or others) and frequently used algorithms (such as search, classification, image processing, or others) using a high-level programming language (Python will be used for examples and exercises). The principles of software design and analysis of the complexity of algorithms will be discussed. At the end of this course, the student is fully prepared to take the PCEP - Python certified entry-level Python programmer from the Python Institute and with some additional preparation, the PCAP - Certified Associate in Python Programming.

MIT 588: Software Development and Management (Fall "C" 2022)

This course examines the fundamental concepts that comprise the information system (IS) functions in business and society, with emphasis on systems analysis & design. Together, we will study, discuss, analyze, and perform various exercises that bring into focus the myriad issues related to this most important field of study that affects virtually all aspects of business and society.

MIT 710: Final Capstone Project (Fall "C" 2022)

The Capstone Field Project provides students with the opportunity to complete their academic curriculum through the real-life application of best practices learned through courses taken in the program. The main objective of the Capstone Field Project is to strengthen the students’ capacities to explore, conceptualize, analyze, explicate, interpret, and provide suggested solutions to companies and organizations facing critical computer engineering challenges.

MIT 537: Risk and Information Systems Control (Fall "C" 2022)

This course aims to identify, assess and evaluate risk to enable the execution of the enterprise risk management strategy; develop and implement risk responses to ensure that risk factors and events are addressed in a cost-effective manner and in line with business objectives; monitor risk and communicate information to the relevant stakeholders to ensure the continued effectiveness of the enterprise’s risk management strategy; design and implement information systems controls in alignment with the organization’s risk appetite and tolerance levels to support business objectives; monitor and maintain information systems controls to ensure they function effectively and efficiently; and achieve professional qualification as Certified in Risk and Information Systems Control (CRISC).


MET 520: Cloud Computing and Data Analytics (Fall "C" 2022)

This course provides a comprehensive understanding to the world of big data and analytics. Big data is now a reality, the volume, variety, and velocity of data coming into the enterprise continues at an unprecedented level. Data analytics is the process of examining data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions. In this course, students will learn how to connect and visualize complex data by utilizing techniques such as aggregators, time series, dashboard customization, storytelling, metadata grids, dual axis charts, etc. Basic statistical methods will be used such as regression, central tendency, and dispersion.