Modern data analytics program focusing on big data, artificial intelligence, machine learning, and advanced analytical techniques.
The Program Learning Outcomes of the Data Analytics program are based on ABET Student Learning Outcomes. They describe what students know and able to do upon completion of the curriculum. Graduates will be able to:
PLO#1: Analyse a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
PLO#2: Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of data analytics.
PLO#3: Communicate effectively in a variety of professional contexts.
PLO#4: Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
PLO#5: Function effectively as a member or leader of a team engaged in activities appropriate to data analytics.
PLO#6: Apply theory, techniques, and tools throughout the data analysis lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.
Advanced track 70% or Elite track 65%, English proficiency 80% or IELTS 5.0, Mathematics 70%, Physics 70%, pass admission test in Mathematics and Physics
The Bachelor of Science degree in Data Analytics requires the completion of 123 credit hours distributed according to the following plan:
| Type of Courses | Credit Hours |
|---|---|
| 1. General Education Requirements | |
| (a) University Compulsory Courses | 18 |
| (b) University Elective Courses | 12 |
| 2. Data Analytics Program Courses | |
| (a) Mathematics and Statistics Courses | 15 |
| (b) Program Core Courses | 66 |
| (c) Program Elective Courses | 9 |
| (d) Internship | 3 |
| Total Credit Hours | 123 |
