Bachelor of Computer Science (Honours) (Data Science)
- Key Information
Course Name:
Bachelor of Computer Science (Honours) (Data Science)
University Name:
Nilai University
Campus:
Nilai
Qualification:
Bachelor
Duration:
3 years
Intake:
January, June, September
IELTS:
5.0
Study Mode:
On-campus
Study Type:
Full time study
Program Mode:
Coursework
Yearly Tuition Fees
| Year | Fee |
|---|---|
| 1st Year | MYR 20,000 |
| 2nd Year | MYR 20,000 |
| 3rd Year | MYR 20,000 |
Other Fees
| Description | Fee |
|---|---|
| Application Fee | MYR 700 |
| Caution Fee (Refundable) | MYR 1,500 |
| International Student Admission Fee | MYR 6,500 |
| Registration Fee | MYR 500 |
| Resource Fee (Yearly) | MYR 3,300 |
| Visa and Insurance/td> | MYR 2,900 |
Campus
Nilai
Qualification
Bachelor
Duration
3 years
Intake
January, June, September
IELTS
5.0
Study Mode
On-campus
Study Type
Full time study
Program Mode
Coursework
Course Fee for International Students
Yearly Tuition Fees
| Year | Fee |
|---|---|
| 1st Year | MYR 20,000 |
| 2nd Year | MYR 20,000 |
| 3rd Year | MYR 20,000 |
Other Fees
| Description | Fee |
|---|---|
| Application Fee | MYR 700 |
| Caution Fee (Refundable) | MYR 1,500 |
| International Student Admission Fee | MYR 6,500 |
| Registration Fee | MYR 500 |
| Resource Fee (Yearly) | MYR 3,300 |
| Visa and Insurance/td> | MYR 2,900 |
Course Overview
The Bachelor of Computer Science (Hons) with a specialization in Data Science at Nilai University offers a rigorous pedagogical framework designed to ground students in the mathematical foundations and computational methodologies of the data-driven era. The program facilitates a transition from general computing to specialized analytical proficiency by synthesizing scholarly inquiry with applied project-based learning, ensuring that candidates can navigate the complexities of modern information ecosystems. The curriculum is strategically structured to provide a comprehensive mastery of critical data-centric pillars: Statistical Analysis and Probabilistic Modeling: Cultivating the quantitative rigor required to derive valid inferences from structured and unstructured data. Machine Learning and Predictive Analytics: Developing the capacity to architect and deploy sophisticated algorithms that facilitate automated decision-making. Big Data Infrastructure and Management: Establishing a thorough understanding of distributed computing frameworks and the management of high-volume, high-velocity data architectures. Data Mining and Knowledge Discovery: Mastering the techniques required to identify patterns, anomalies, and correlations within vast “huge data” repositories. By integrating technical expertise with systematic problem-solving methodologies, the program equips candidates with the professional competencies required to excel in a data-centric global economy. Graduates emerge as versatile practitioners prepared for pivotal roles as Data Scientists, Business Intelligence Analysts, or Machine Learning Engineers, possessing the prerequisite academic rigor to pursue advanced postgraduate research in specialized domains such as Artificial Intelligence or Neural Networks.
Curriculum
Programme Structure
| Category | Modules Offered |
|---|---|
| Foundational & Core Programming |
|
| Systems & Infrastructure |
|
| Software Engineering & Design |
|
| Theoretical & Advanced Computing |
|
| Data Science Specialisation |
|
| Capstone & Training |
|
| University Requirements (MPU) |
|
Field of Research
N/A