Graduate Degree Programs

Doctor in Information Technology

The Doctor in Information Technology (DIT) program is a three-pronged postgraduate course designed to equip candidates with knowledge and skills needed to become agents for societal and organizational change through the planning, management, and implementation of IT in ways that are theoretically grounded, relevant, innovative, critical, and ethical.

The course seeks to bridge professional relevance (practice) with conceptual grounding (theory) and aims at developing a breed of professionals who can seamlessly link three domains: social and organizational knowledge, technical expertise, and ethics. A key assumption of the course is that changes in society are most effectively achieved by working through reshaping its most significant institutions. In this course, emphasis is placed on equipping students to understand, plan, and manage IT interventions in business, academic, and government settings.

In the course of taking the program, students will depart from popular and oversimplified models that view the IT processes as linear, predicable, revolutionary, utopian, and deterministic. They will increasingly understand that technology is complex, socially shaped, value-laden, and capable of being harnessed for diverse goals, which in turn are not equally desirable in terms of their normative implications. At the end of the program, successful candidates can then become change agents in different capacities: as policy makers, chief information officers, high-level lecturers or researchers, heads of organizations, or officers in charge of large departments.

• Admission Requirements
• Degree Requirements
• Academic Program Components

Admission Requirements

The program accepts applicants who have a relevant Master’s degree and two years of relevant work experience. Master’s degrees from the following fields are considered ideal (others may be considered on a case-to-case basis):

1. MSIT/MSCS/MCS/MIT
2. MBA/Master in Public Administration/Master in Education
3. Master of Science in Engineering, Math, Science, or Statistics

Note:

• All applicants must have middle-level management, teaching, or research experience.
• For those with non-CS or non-IT master degrees, applicants must have some background in IT specifically in information systems development and information systems planning.
• Since the program will be administered in English, students are expected to demonstrate a strong grasp of the language. Applicants may be required to submit their TOEFL results.

Degree Requirements

The DIT degree is obtained primarily through supervised research. It is awarded upon fulfillment of the following requirements:

• completion of all academic courses
• pass the oral comprehensive examination
• submission of a doctoral dissertation based on an independent, original research
• successful defense of the doctoral dissertation
• one (1) local and one (1) international publication, or two (2) published and presented papers related to the dissertation topic before final defense
• fulfillment of residency and other University requirements

Academic Program Components

Remedial/Bridging courses (12 units) 

• Project Management and IS Development
• IT Strategy and Governance
• Innovation, Organizational Change, and Entrepreneurship
• IT Service Management

Foundation courses (9 units) 

• An Overview of IT in Society
• Social, Organizational, and Ethical Theories and Applications
• Theoretical Approaches to IT

Specialized/Required courses (9 units) 

• Internet and Information Infrastructure
• Enterprise Architecture
• Data Science and Data Analytics

Elective courses (3 units)

• Special Topics in Disaster Management
• Special Topics in Healthcare Informatics
• Special Topics in Business Process Innovation
• Special Topics in Game Development

Case Study and Immersion (3 units)
Methods of Research (3 units) 
Dissertation Writing and Defense (12 units) 

Total: 39 units

 

Doctor of Philosophy in Computer Science

The Doctor of Philosophy in Computer Science (PhDCS) program is designed to develop scientists capable of conducting independent research in Computer Science. Courses are organized depending on the research interest of each candidate for a deeper knowledge of Computer Science as well as ample preparation for scientific research in a chosen field of specialization. As part of a sandwich program, a PhD candidate is encouraged to spend 3 to 12 months of dissertation research at a host university in a foreign country for opportunities to discuss research work with international experts.

• Admission Requirements
• Degree Requirements
• Academic Program Components

Admission Requirements

The program accepts applicants who have an MS in Computer Science degree with research-based thesis and at least one research-based paper published in a national or international refereed CS conference.

Master’s degrees from the following fields may be considered for entry into the program (others may be considered on a case-to-case basis) upon completion of the required remedial coursework/s:

1. MS in Computer Science (MSCS) without a research-based thesis
2. Master in Computer Science (MCS)
3. MS in Information Technology (MSIT)
4. BSCS with an MS degree in another field
5. BS and MS degree in another field but with IT experience

Note:

• For (1) and (2), applicants must undergo 6 units remedial coursework, and 3 units Methods of Research.
• For (3), (4), and (5), applicants must undergo 15 units remedial coursework and 3 units Methods of Research.

In addition, the applicant should have a GPA of at least 80% or equivalent in the MS course. For foreign applicants from non-­English speaking countries, a TOEFL score at least 550 is required.

Degree Requirements

The PhD degree in Computer Science is obtained primarily through supervised research. It is awarded upon fulfillment of the following requirements:

• completion of all academic courses
• pass the oral comprehensive examination
• submission of a doctoral dissertation based on an independent, original research
• successful defense of the doctoral dissertation
• publication of a full paper on the dissertation research in a reputable refereed international scientific journal or from a tier 1/2 ISI/Scopus-indexed CS conference with the PhD candidate as first author
• fulfillment of residency and other University requirements

Academic Program Components

For applicants with a degree of Master of Science in Computer Science with a research-based thesis:

Specialized courses	24 units
Doctoral dissertation	12 units
Total	36 units

For applicants with a degree of Master of Science in Computer Science or Master in Computer Science without a research-­based thesis, the following are the remedial academic requirements before entering into the PhD program proper:

Remedial courses	6 units
Methods of Research	3 units

Plus a research-based paper published in a national or international refereed CS conference.

For applicants with a degree of Master of Science in Information Technology, or BSCS with a non-­MSCS degree, or non-­BSCS and non-­MSCS degree but with IT experience, the following are the remedial academic requirements before entering into the PhD program proper:

Remedial courses	15 units
Methods of Research	3 units

Plus a research-based paper published in a national or international refereed CS conference.

Note:

Remedial courses can be MSCS Foundation courses or electives as defined by the Graduate Program Coordinator on a case-­to-­case basis.

 

Master of Science in Computer Science

The Master of Science in Computer Science (MSCS) program is a two-year post-graduate course designed to train students in undertaking high-level research in the advanced field of computing. In the course of the program, students develop a rigorous and deeper understanding of the theoretical and underlying principles of computation in the areas of programming languages, computer architecture, operating systems, algorithms and complexity, automata, and intelligent systems. By engaging students to work in research laboratories, they are further equipped with technical project management skills to lead in the advancement of computer science research.

The program makes extensive use of published research papers and journals to encourage students to develop new or adapt existing algorithms, and to explore their innovative applications in various domains. These heavily rely upon independent research by students, and provide opportunities to integrate theories and disseminate research results to local and international audiences.

Students coming from non-CS and non-IT academic backgrounds who wish to take the program are prepared through a series of remedial courses. Candidates’ understanding of the theories in computing, and their proficiency and style in written and oral communication are primarily attested to by the successful completion and defense of a master’s thesis.

The program is an appropriate preparation for those aspiring to discover new approaches to solving a computing problem, and to make an existing technology adapt to new application areas; for those seeking a career in the dynamic field of computing; and for those intending to develop their skills in conducting research and further studies at the doctoral level.

• Admission Requirements
• Degree Requirements
• Academic Program Components

Admission Requirements

The program accepts applicants who have a Bachelor’s degree in Computer Science or ITE allied fields (e.g. sciences, math, and engineering). Other Bachelor’s degrees may be considered on a case-to-case basis.

Note:

• Applicants may be required to take remedial courses depending on their degree or courses they have taken up during their Bachelor’s degree.
• Since the program will be administered in English, students will be expected to demonstrate a strong grasp of the language.

Degree Requirements

The MSCS program is obtained primarily through supervised research. It is awarded upon fulfillment of the following requirements:

• completion of all academic courses
• pass the oral comprehensive examination
• submission of a master’s thesis based on an independent, original research
• successful defense of the master’s thesis
• publication in a reputable refereed international scientific journal or from an ISI/Scopus-indexed CS conference
• fulfillment of the residency and other University requirements

Academic Program Components

The program is composed of 12 units of remedial courses (optional), 15 units of foundation courses, 3 units of Methods of Research, 12 units of elective courses, oral comprehensive exam, and 6 units of thesis.

Remedial Courses (12 units)*

• Data Structures and Algorithms
• Operating Systems
• Computer Organization
• Intelligent Systems

Foundation Courses (15 units)

• Advanced Operating Systems
• Advanced Computer Architecture
• Advanced Automata and Complexity
• Theories of Programming Languages
• Design and Analysis of Algorithms

Elective Courses (12 units)

• Artificial Intelligence and Machine Learning
• Neural Networks
• Natural Language Processing
• Data Science
• Empathic Computing
• User Modeling
• Human-Computer Interaction
• Bioinformatics
• Augmented and Virtual Reality
• Complex Systems
• Digital Signal Processing
• Computer Vision and Pattern Recognition
• Internet-of-Things
• Cybersecurity

Oral Comprehensive Exam (0 units)

Thesis (6 units)**

Note:

* Not included in the count of total academic units. These are optional courses added to the study plan upon recommendation of the Graduate Program Coordinator and approval of the Department Chair.

** A student must produce a published paper in a Scopus-indexed conference proceeding or a journal article related to any or all aspects of their thesis as part of the completion requirements.

 

 

Master of Science in Data Science

Data science emerged as a result of the proliferation of vast data sets in various fields, leading to the need for automated methods to facilitate efficient and effective data analysis by humans. The Master of Science in Data Science (MSDS) program equips individuals with the necessary expertise to collect, manage, analyze, and visualize data, enabling them to make informed and ethical decisions driven by data. It draws upon the convergence of computer science, statistics, and domain-specific knowledge to address real-world challenges and find practical solutions.

Graduates of the program can explore different roles in the field of data science, such as:

• • Data Engineer
  • Data Scientist
  • Machine Learning Engineer
  • Business Intelligence Developer
  • Data Steward
  • Data Storyteller

• Program of Study
• Admission Requirements
• Degree Requirements
• Course Details

Program of Study

The Data Science graduate program has six (6) core courses and students are able to customize their learning experience through four (4) electives. The courses are scheduled across three (3) terms for full-time students and five (5) terms for part-time students. In addition to the academic units, the program also requires passing the comprehensive examination and publication of the research output.

The core courses include: 

• Principles of Data Science
• Data Visualization
• Data Governance, Ethics and Privacy
• Machine Learning for Data Science
• Big Data and Scalable Computing
• Research Methods

The program allows students to choose from different tracks, namely: 

• Big Data Analysis track
• Applied Machine Learning track
• Business Analytics and Business Intelligence track

Admission Requirements

To be eligible for consideration to the MSDS program, one must hold a Bachelor’s degree from an accredited institution, which includes a minimum of four years of full-time study. Admission to the program that is different from the individual’s undergraduate program of study may require completion of prerequisite courses before commencing graduate-level coursework. Due to the technical nature of the program, students are expected to have a strong technical background, typically with an undergraduate degree in STEM.

Degree Requirements

The MSDS degree is awarded upon fulfillment of the following requirements:

• completion of all academic courses
• pass the oral comprehensive examination
• submission of a master’s thesis based on an independent, original research
• successful defense of the master’s thesis
• publication in a reputable refereed international scientific journal or from an ISI/Scopus-indexed CS conference
• fulfillment of residency and other University requirements

Course Details

• Principles of Data Science (DATA100). This is an introductory course designed to provide students with the basic concepts of data analysis and statistical computing to explore interesting issues and problems. The course is designed for entry-level students from any major, specifically for students who have not previously taken any statistics or computer science courses.
• Data Visualization (DATA101). This course explores the design and creation of data visualizations based on available data and tasks to be achieved. This process includes basic data modeling, processing, mapping data attributes to graphical attributes, and strategic visual encoding based on known properties of visual perception as well as the tasks(s) at hand. Students will also learn to evaluate the effectiveness of visualization designs, and think critically about each design decision, such as choice of color and visual encoding.
• Data Mining and Statistics (DATA102). This course studies algorithms and computational paradigms that allow computers to find patterns and regularities in databases, and generally improve their performance through interaction with data. This course includes data selection, cleaning, and using different statistical techniques. The course will cover all these issues and will illustrate the whole process with examples. Data mining mostly handles tabular data because of its roots in knowledge discovery in databases, but is not limited to it.
• Introduction to Machine Learning (DATA103). Machine learning is the automatic induction of new information from large amounts of data to make predictions or decisions without human intervention. This course introduces the students to a broad cross-section of models and algorithms for machine learning, and equips them with skills to discover new information from volumes of data. Data mining and machine learning have overlapping algorithms and methods, but they focus on different things: data mining focuses on finding patterns while machine learning focuses on predictive models.

 

Master in Information Technology

Today’s rapid advancement in information and communications technology (ICT) continues to induce change in an unprecedented rate. Being seen as an ongoing information revolution, these changes open opportunities for motivated individuals who have taken the initiative to enhance their current qualifications with market-oriented skills and expertise.

Anchored on the idea of a holistic professional development, the Master in Information Technology (MIT) program combines knowledge in organizational systems, information security, information management, and service management. Based on a multidisciplinary curriculum, the program shall equip professionals with the necessary tools, knowledge, skill requirements, and understanding of the latest technologies that are being used in today’s business-organizational environment. The program also addresses  the behavioral, managerial, and technical aspects of ICT in the context of organizational systems.

The MIT program is designed to address the rapid rise in demand for professionals versed in information technology, information security, risk management, and service management, by offering that courses that would enable students to make immediate contributions to the workplace.

• Admission Requirements
• Degree Requirements
• Academic Program Components

Admission Requirements

The program accepts applicants who have a relevant Bachelor’s degree in Computer Science or ITE allied fields and one year of IT-related work experience. Other Bachelor’s degrees may be considered on a case-to-case basis.

• Applicants may be required to take remedial courses depending on their degree or courses they have taken up during their Bachelor’s degree.
• Since the program will be administered in English, students will be expected to demonstrate a strong grasp of the language. Applicants may be required to submit their TOEFL results.

Degree Requirements

The MIT degree is obtained primarily through supervised research. It is awarded upon fulfillment of the following requirements:

• completion of all academic courses
• pass the oral comprehensive examination
• submission of a capstone project
• successful defense of the capstone project
• fulfillment of residency and other University requirements

Academic Program Components

Remedial/Bridging courses (18 units)

• Project Management and IS Development
• IT Resource Management
• Basics of Databases
• Basic Programming
• Advanced Programming
• Introduction to Software Engineering

Foundation courses (15 units)

• Advanced OS and Networking
• Advanced Systems Design and Implementation
• Technology and Project Management
• IS Architecture
• IT Service Management

Elective courses (15 units)

• Enterprise Architecture
• Business Intelligence and Analytics
• Risk Management and Business Continuity Planning
• Information Security and Regulatory Compliance
• Emerging Trends in Computing
• Informatics, Shared, and Collaborative Systems

Capstone Project Proposal (3 units)

Capstone Project Final (3 units)

Total: 36 units

 

 

Master in Information Security

Admission Requirements

The program accepts applicants who have a relevant Bachelor’s degree in Computer Science or ITE allied fields and one year of IT-­related work experience or two years relevant work experience. Other Bachelor’s degrees may be considered on a case-­to-case basis.

• Applicants may be required to take remedial courses depending on their degree or courses they have taken up during their Bachelor’s degree.
• Since the program will be administered in English, students will be expected to demonstrate a strong grasp of the language. Applicants may be required to submit their TOEFL results.

Note: Applications are accepted exclusively for Term 1 admissions.

Degree Requirements

The Master in Information Security degree is awarded upon fulfillment of the following requirements:

• completion of all academic courses
• pass the oral comprehensive examination
• completion of two (2) major integrative projects
• successful defense of the capstone project
• fulfillment of residency and other University requirements

Academic Program Components

Foundation Courses (8 units)

• IT Foundations (Networks, Database, System Administration)
• Introduction to Information Security
• Technical Writing for IT