Advanced AI Knowledge
PEO1: Apply advanced knowledge in data science, machine learning, and artificial intelligence to design, develop, and implement innovative solutions to complex technological and business problems.
Our Programs
Master of Science in Information Technology
Master of Science in Information Technology (MSIT - 2 Year)
Master's Degree
Level 7 · 54 Credits · 6 Terms · 2 Years
Master of Science in Information Technology (MSIT)
The Master of Science in Information Technology (Data Science) program provides a rigorous academic foundation in key areas such as machine learning, deep learning, and data science. The program aims to equip students with the skills necessary to analyze and interpret complex datasets, develop intelligent systems, and apply innovative solutions in various technological contexts. Students will explore various AI models and algorithms, statistical modeling, and data-driven decision-making models. The curriculum fosters critical thinking and technical proficiency, preparing graduates to excel in research, development, and industry applications. This program aims to produce entrepreneurs capable of initiating startups and shaping the tech industry through the use of the latest AI technology.
The program's comprehensive structure includes specialized courses such as Natural Language Processing, Deep Learning, Machine Learning, Big Data Analytics, Python Programming, Human-Computer Interaction, Connective Computing, AI Security, Ethic & Policy Development, and IoT Forensics and Security allowing students to gain expertise in high-demand areas. Industry partnerships provide real-world experience, enhancing learning and employability. Students will also engage in collaborative projects, encouraging teamwork and interdisciplinary problem-solving. Graduates will be well-positioned for careers in academia, technology firms, and beyond, driving innovation and contributing to advancements in the field.
🤖 Natural Language Processing & Deep Learning
📊 Big Data Analytics & Python
🚀 UniPreneur Tech Startups
🛡️ AI Security, Ethics & Policy
Program Educational Objectives (PEOs)
Professional Careers
PEO2: Pursue successful careers as data scientists, AI/ML engineers, researchers, or technology leaders in a wide range of industries, both locally and internationally.
Entrepreneurial Capability
PEO3: Demonstrate entrepreneurial capability by initiating startups, leading technology-driven ventures, or introducing innovative AI-based products and services to the market.
Research & Advancement
PEO4: Conduct research and contribute to advancements in data science and emerging technologies, engaging in continued learning to stay current with evolving tools, techniques, and industry trends.
Ethical Judgment
PEO5: Practice their profession with strong ethical judgment and social responsibility, considering the implications of data use and AI deployment on individuals, organizations, and society.
Effective Leadership
PEO6: Communicate effectively and collaborate across disciplines and teams, exercising leadership in academic, industry, and community settings.
Program Learning Outcomes (PLOs)
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1 PLO1
Demonstrate proficiency of understanding the foundational principles of emerging technology including computing, data science and AI. -
2 PLO2
Demonstrate proficiency in applying statistical and algorithm techniques to analyze and model large datasets, extracting meaningful insights and making predictions. -
3 PLO3
Apply advanced computational techniques and tools, such as artificial intelligence, cloud computing and machine learning algorithms to solve complex, real-world problems. -
4 PLO4
Interpret the results of data analyses, recognizing patterns, trends, and anomalies that provide insights into business, scientific, or social phenomena. -
5 PLO5
Demonstrate the ability to critically evaluate the ethical implications of data collection, analysis, and use, ensuring responsible practices in the data science field. -
6 PLO6
Demonstrate the ability to communicate and report clear, detailed descriptions of complex subjects in the English language to a range of audiences.
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7 PLO7
Solve problems effectively, both individually and collaboratively, demonstrating leadership to deliver innovative and practical solutions. -
8 PLO8
Apply critical thinking, entrepreneurship, and research skills to design logically structured and modular solutions to problems. -
9 PLO9
Evaluate the existing computing technologies and tools to determine their appropriateness in solving real-world problems. -
10 PLO10
Apply mathematical and statistical techniques to analyze and resolve complex computing issues. -
11 PLO11
Interpret data representation and transformations for decision making.
Why MSIT at UP
Academic Excellence
Our curriculum is benchmarked against leading ASEAN universities and continuously refined with industry partners.
Advanced AI & Deep Learning
Hands-on training with state-of-the-art neural networks, NLP, and machine learning frameworks.
Big Data & Hadoop Infrastructure
Master distributed file systems, cloud analytics (AWS/Huawei), and enterprise business intelligence.
UniPreneur & Startup Incubation
Turn AI research into viable commercial startups through UP's UniPreneur incubation track.
AI Security & Ethics
Rigorous grounding in AI policy, security, governance, and ethical data science practices.
Research Project Thesis
135-hour mentored research project solving real-world technological challenges.
Industry Partnerships
Collaborative projects and joint research with leading regional tech enterprises and international universities.
Where Graduates Go
Career Pathways
Upon completion of this program, graduated students could have opportunities for the following employment:
AI & Data Engineering
Data Scientist
Machine Learning Engineer
Artificial Intelligence Engineer
Data Analyst
Statistical Analyst
Data Science Researcher
Architecture & Systems Design
Data Architect
Enterprise Architect
Applications Architect
Senior Data Consultant
Storage Engineer
DevOps, Security & Emerging Tech
DevOps Engineer
Cybersecurity Operation Analyst
Forensic Investigator
Blockchain Engineer
Admissions
Admission Criteria & Fees
Admission Requirements
- Completed UP application form
- Bachelor's degree in IT related field or equivalent degree
- Pass Entrance exam testing two subjects: Computer Science and English
- Official academic transcripts and national ID / passport copy
Tuition & Program Structure
Master's Degree Tuition
USD 1,950 / year
Program Duration
2 Years (6 Terms, Level 7)
Total Credits
54 Credits
Entrance Subjects
Computer Science & English
Student Stories
Master's Student Voices
"The MSIT program provided me with deep mathematical and practical tools to build production machine learning models. The research project opened doors to international collaboration."
"Thanks to the UniPreneur course and hands-on AI modules, my team launched an intelligent analytics platform right after completing our Master's degree."
"The MSIT program provided me with deep mathematical and practical tools to build production machine learning models. The research project opened doors to international collaboration."
"Balancing work and study was seamless. The curriculum in Hadoop, Business Intelligence, and Data Security directly elevated my role at work."
Campus Life
Media & Gallery
Our Experts
Staff Members
Prof. Dr. Tam Sakirin
Dean, Faculty of Science & Technology
PhD (Computer Science)
Mrs. Chem Sokea
Senior Lecturer, Data Science & AI
MSc (Software Engineering & Data Mining)
Ms. Nuon Roatny
Lecturer, Cloud & Cyber Security
MSc (Network & AI Security), CCNA
Need More Information?
Contact Faculty of Science & Technology
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