Course Structure
The programme encompasses a range of units that cover essential aspects of PhD in AI and Machine Learning, ensuring students acquire a comprehensive skill set. The units offered are as follows:
| S/N | Unit Reference | Unit Title | Credits |
|---|---|---|---|
| 1 | DCT 700 | Doctoral Studies Seminar | 3 |
| 2 | BTC 701 | Organizational Resilience Framework | 3 |
| 3 | BTC 770 | Navigating Conflict And Risk For Positive Leadership | 3 |
| 4 | IT 701 | Innovation, Risk, And Cybersecurity | 3 |
| 5 | IT 707 | Special Research Topics In Technology | 3 |
| 6 | MGT 765 | High Performance Leadership | 3 |
| 7 | RES 711 | Research Methods: Introduction And Scope | 3 |
| 8 | RES 712 | Qualitative And Exploratory Research Methods | 3 |
| 9 | RES 713 | Quantitative Research Methods I: Data Management And Non-Experimental | 3 |
| 10 | RES 714 | Quantitative Research Methods II: Experimental And Statistical | 3 |
| 11 | DIS 796 | Dissertation I - Chapter 1 | 3 |
| 12 | DIS 797 | Dissertation II - Chapter 2 | 3 |
| 13 | DIS 798 | Dissertation III - Chapter 3 | 3 |
| 14 | DIS 799 | Dissertation IV - Chapter 4 | 3 |
| 15 | DIS 800 | Dissertation V - Chapter 5 | 3 |
| 16 | - | Introduction To Business Analytics | 3 |
| S/N | Unit Reference | Unit Title | Credits |
|---|---|---|---|
| 1 | RSD 801 | Doctoral Residency I | 1 |
| 2 | RSD 802 | Doctoral Residency II | 1 |
| 3 | RSD 803 | Doctoral Residency III | 1 |
| S/N | Unit Reference | Unit Title | Credits |
|---|---|---|---|
| 1 | IT 720 | Applied Research In Natural Language Processing | 3 |
| 2 | IT 721 | Applied Research Topics In Deep Learning Theory & Practical Applications | 3 |
| 3 | IT 722 | Advanced Topics In Data Storage & Mining | 3 |
| 4 | IT 723 | Advanced Programming For Data Analysis | 3 |
Specialisation: AI & ML
Strengthen your expertise in the most sought-after AI fields:
Natural Language Processing (NLP): Explore text analytics and speech recognition applications.
Deep Learning: Delve into neural networks, advanced algorithms, and emerging machine learning paradigms.
Data Storage & Mining: Master the art of handling large-scale data, identifying trends, and deriving insights.
Advanced Programming: Enhance your capabilities in building and refining AI and analytics tools.
Career Outcomes
Graduates can pursue impactful roles such as:
AI Research Scientist
Chief Data Officer (CDO)
University Professor or Researcher
Machine Learning Architect
Data Strategy Consultant
Director of Innovation or Technology
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🌐 Global Accreditation & Recognition
- Walsh College is accredited by the Higher Learning Commission (HLC)
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