Embark on a transformative journey with Walsh College’s PhD in Technology, specializing in Artificial Intelligence and Machine Learning. This program prepares you to lead in a rapidly evolving field, combining flexible online coursework with advanced research in areas like natural language processing and deep learning. Graduate as a visionary leader, ready to drive technological advancements in an era shaped by intelligent systems and data-driven insights.
The Doctor of Philosophy in Technology (Tech PhD) is an advanced academic degree designed for those aiming to excel in the technology sector. Graduates will develop the expertise required for leadership roles as technology innovators, consultants, and educators. The program emphasizes significant research, allowing students to explore cutting-edge technology topics and apply their knowledge to solve complex challenges. The part-time structure, tailored for working professionals, offers online coursework and remote delivery through platforms like Zoom, with on-site engagement opportunities for those near the campus.
The Tech PhD curriculum blends theoretical foundations with practical applications, preparing students to address real-world technological dilemmas. The program spans 60 semester hours, beginning with foundational Research and Methods courses. After completing the core research methodology, candidates take a Preliminary Exam within two semesters. Upon passing, they proceed to the dissertation phase, dedicating 15 hours to original research. The program equips students with the tools and insights to lead with innovation and make impactful contributions to technology and society.
3 Years PhD Degree
AED 68,775 / Year
*VAT 5% inclusive
| DCT 700 | Doctoral studies seminar | 3 |
| BTC 701 | Organizational resilience framework | 3 |
| BTC 770 | Navigating conflict and risk for positive leadership | 3 |
| IT 701 | Innovation, risk, and cybersecurity | 3 |
| IT 707 | Special research topics in technology | 3 |
| MGT 765 | High performance leadership | 3 |
| RES 711 | Research methods: introduction and scope | 3 |
| RES 712 | Qualitative and exploratory research methods | 3 |
| RES 713 | Quantitative research methods i: data management and non-experimental | 3 |
| RES 714 | Quantitative research methods ii: experimental and statistical | 3 |
| DIS 796 | Dissertation i - chapter 1 | 3 |
| DIS 797 | Dissertation ii – chapter 2 | 3 |
| DIS 798 | Dissertation iii – chapter 3 | 3 |
| DIS 799 | Dissertation iv- chapter 4 | 3 |
| DIS 800 | Dissertation v – chapter 5 | 3 |
| Introduction to Business Analytics | 3 |
| RSD 801 | Doctoral Residency I | 1 |
| RSD 802 | Doctoral Residency II | 1 |
| RSD 803 | Doctoral Residency III | 1 |
| IT 720 | Applied Research In Natural Language Processing | 3 |
| IT 721 | Applied Research Topics In Deep Learning Theory & Practical Applications | 3 |
| IT 722 | Advanced Topics In Data Storage & Mining | 3 |
| IT 723 | Advanced Programming For Data Analysis | 3 |
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Admissions/Advising | IT and Cybersecurity by Tara Weiner | November 2,2023
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