Quick Facts
Duration
3 years
Mode
Full-time, On-campus
Intake
Jan, Feb*, Mar*, Apr*, May, Jun*, Jul*, Sep, Nov*
*This may be a special intake. Contact us to find out more.
Tuition Fees
RM51,075
Course Structure
SEMESTER 1 (Y1/S1)
- BIT 1023 – Introduction to Multimedia
- BIT 1063 – Discrete Mathematics
- Elective 1: (Choose one)
- Fundamentals of Cryptography
- Introduction to Data Science
- AI and Its Application
SEMESTER 2 (Y1/S2)
- BIT 1053 – Computer Programming
- BIT 1073 – Software Engineering
- Elective 2: (Choose one)
- Information Security Assurance
- Introduction to R
- Machine Learning in AI
SEMESTER 3 (Y1/S3)
- BIT 1013 – Fundamental of Information Technology
- BIT 1043 – Professional Communication in IT
- Elective 3: (Choose one)
- Computer Intrusion Detection
- Introduction to Machine Learning
- Data Wrangling and Visualization
SEMESTER 4 (Y2/S4)
- BIT 1083 – Data Structure
- BIT 1103 – Operating Systems
- BIT 1123 – Object-Oriented Programming
- BIT 2033 – Systems Analysis and Design
- BIT 2093 – Computer Architecture
- Elective 4: (Choose one)
- Digital Forensics
- Big Data Analytics
- Deep Learning
SEMESTER 5 (Y2/S5)
- BIT 4033 – Cloud Foundation
- BIT 2023 – Data Warehousing
- BIT 2053 – Fundamentals of Modern Data
- BIT 2063 – Computer Communication and Networks
- BIT 4023 – Web Programming
- Elective 5: (Choose one)
- Penetration Testing and Vulnerability Assessment
- Data Visualization
- Natural Language Processing
SEMESTER 6 (Y2/S6)
- BIT 2073 – Human Computer Interaction
- BIT 3083 – Software Project Management
- Elective 6: (Choose one)
- Ethical Hacking
- Data Mining
- Generative AI
SEMESTER 7 (Y3/S7)
- BIT 3013 – Cyber Security
- BIT 3023 – Network Management
- BIT 3042 – Project 1
- BIT 4013 – Introduction to Mobile App Development
- Elective 7: (Choose one)
- Security Analytics & Incident Response
- Data Warehousing in Data Science
- Intelligence, Responsible AI, and Ethics
SEMESTER 8 (Y3/S8)
- BIT 3044 – Project 2
- Elective 8: (Choose one)
- Cyber Threat Intelligence
- Exploratory Data Analysis
- AI for Technology Venture
SEMESTER 9 (Y3/S9)
- BIT 4016 – Industrial Training
Entry Requirements
- Matriculation / Foundation studies: A pass with minimum CGPA of 2.0 and a credit in Mathematics at SPM level or its equivalent
- STPM: A pass with a minimum Grade C (GP 2.0) in any 2 subjects and a credit in Mathematics at SPM level or its equivalent
- Diploma in Computer Science / Software Engineering / Information Technology / Information Systems or equivalent: Minimum CGPA of 2.5 and a credit in Mathematics at SPM level or its equivalent
- Any other Diploma in Science and technology or business studies: Minimum CGPA of 2.5 may be admitted, subject to a rigorous internal assessment process and a credit in Mathematics at SPM level or its equivalent
- DKM/DLKM/DVM: A Pass (HEP is required to implement a screening and bridging programme which corresponds to the programme field).
Notes
- Candidates with CGPA below 2.5 but above 2.0 with a credit in Mathematics at SPM level or its equivalent may be admitted, subject to a rigorous internal assessment process.
- Requirement for credit in Mathematics at SPM level of the candidate may be exempted if the qualification contains Mathematics subject and its achievement as the equivalent/higher than the subject credit requirement at SPM level.
- Candidate with a credit in computing related subject at SPM or STPM level or its equivalent may be given preferential consideration
International Students (Senate Minimum Requirements)
- IELTS: Minimum score of 5.0
- MUET: Band 3.5 or its equivalent
Estimated Fees
Application fees (non-refundable)
RM500
Tuition fees
RM51,075
Other miscellaneous fees
RM1,000
Discounts & scholarships
-RM300
Total payable amount
RM52,275
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