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MSc Advanced Computer Science
Key facts
| Qualification | Master's Degree |
| Study mode | Full-time, Part-time |
| Duration | 1 year |
| Intakes | September |
| Tuition (Local students) | $ 13,603 |
| Tuition (Foreign students) | $ 28,443 |
Subjects
-
Computer Science
-
Computer Science, IT
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Duration
1 year
Tuition fees
| Description | Local students | Foreign students |
|---|---|---|
| Tuition fee | $ 13,603 | $ 28,443 |
| Miscellaneous fees | Data not available | Data not available |
| Total estimated cost of attendance | $ 13,603 | $ 28,443 |
| Estimated cost per year | $ 13,603 | $ 28,443 |
Estimated cost as reported by the institution. There may be additional administrative fees. Please contact for the latest information.
Every effort has been made to ensure that information contained in this website is correct. Changes to any aspects of the programmes may be made from time to time due to unforeseeable circumstances beyond our control and the Institution and EasyUni reserve the right to make amendments to any information contained in this website without prior notice. The Institution and EasyUni accept no liability for any loss or damage arising from any use or misuse of or reliance on any information contained in this website.
Admissions
Intakes
Entry Requirements
- A First or Upper Second class honours degree, or the overseas equivalent, in computer science, or in a joint degree with at least 50% computer science content. Applicants with extensive computer science industrial experience and a good honours degree, or its overseas equivalent, may also be considered for admission.
English language
- IELTS score of 6.5 minimum with 6 in all sub-categories
- Internet based TOEFL 100 ibt with no less than 23 in individual components
- Cambridge Proficiency Grade 'C'
- Pearson English overall 59 (writing 51)
- India: Central Board of Secondary Education Senior School Certificate Year VII (GPA >80)
- West Africa Education Certificate (WAEC) Grade C6
- Nigerian Education Council Certificate (NECO) Grade C5
Curriculum
- Research Methods and Professional Skills
- Automated Reasoning and Verification
- Optimization for Learning, Planning and Problem-Solving
- Semi-Structured Data and the Web
- Ontology Engineering for the Semantic Web
- Principles of Digital Biology
- Introduction to Health Informatics
- Parallel Programs and their Performance
- Designing for Parallelism and Future Multi-core Computing
- Data Engineering