Curriculum
The curriculum is designed to be both flexible and comprehensive, allowing students to tailor their studies according to their interests and career goals. Core courses cover the essential aspects of data science, while elective courses allow for specialization in areas such as:
Core Courses
- Data Science Concepts and Machine Learning
- Advanced Data Management
- Big Data and Data Mining
- Neural Networks and Fuzzy Logic
- Statistics and Mathematical Modeling
- Python for Machine Learning
- Professional Practice
- Project Management
- Research Methodology
- Entrepreneurship
- Topics in Emerging Technologies
- AI Techniques and Applications
- Advanced Algorithms
Electives
- Data Visualization and Business Intelligence
- NW Planning, Design, and Management
- Data and Computer Security
Admission Requirements
- A Bachelor’s degree in Engineering, Science, OR Technology in a Computing field obtained from a recognized university
- OR A Bachelor’s degree in any subject area other than mentioned in (a) above, with at least 35% of the total credits of the program being in computing or IT-related subjects, obtained from a recognized university, and a minimum of one-year appropriate experience in a field of computing after graduation
- OR Membership of a recognized professional institute relevant to the field of Computing, obtained through an academic route (SLQF 6), and a minimum of one year of appropriate experience after the membership is obtained
- OR Any other qualifications and experiences acceptable to the Senate.
AND
Pass a selection test conducted by the Department of Electrical and Computer Engineering
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