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EasyUni Sdn Bhd

Level 17, The Bousteador No.10, Jalan PJU 7/6, Mutiara Damansara 47800 Petaling Jaya, Selangor, Malaysia
4.4

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+60142521561

EasyUni Sdn Bhd

Level 17, The Bousteador No.10, Jalan PJU 7/6, Mutiara Damansara 47800 Petaling Jaya, Selangor, Malaysia
4.4

(43) Google reviews

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Diploma in Computer Science

About

The Diploma in Computer Science programme is designed to equip students with broad-based knowledge and future-oriented skills such as Data Science, Cloud Computing, Machine Learning and Programming. These tech disruptive skills are highly sought after by companies not just in the tech industry but also many others worldwide.

Upon completion of this programme, students can join the workforce, become technopreneurs or further their studies at our partner universities in various fields of specialisation such as Software Engineering and Data Science.

Key facts

Statistics
Qualification Diploma
Study mode Full-time
Duration 2.5 years
Intakes January, June, August
Estimated cost per year (local) B$ 7,039
Estimated cost per year (foreign) B$ 7,310

Subjects

  • Computer Science

  • Computer Science, IT

Duration

2.5 years

Tuition fees

Description Local students Foreign students
Tuition fee B$ 7,039 B$ 7,310
Miscellaneous fees B$ 2,286 B$ 4,001
Total estimated cost of attendance B$ 9,326 B$ 11,311
Estimated cost per year B$ 3,730 B$ 4,524

Miscellanous fees explained

Local students

Description Amount
Student Resource Fees B$ 661-B$ 2,406
Application Fee B$ 180
Admission Deposit B$ 150

Foreign students

Description Amount
Visa Application Fees B$ 691
Student Resource Fees B$ 962-B$ 2,406
Application Fee B$ 451
Admission Deposit B$ 902
International Student Fee B$ 3,083

Estimated cost as reported by the institution. There may be additional administrative fees. Please contact us 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

SIJIL PELAJARAN MALAYSIA (SPM)
Min. 3 credits including Mathematics and a pass in Bahasa Melayu and Sejarah (History)

O LEVEL / IGCSE
Min. 3 credits including Mathematics

UEC 
Min. 3Bs including Mathematics

SIJIL TINGGI PERSEKOLAHAN MALAYSIA (STPM)
Min. a Grade C in any subjects and a credit in Mathematics at SPM level or its equivalent 

OTHER QUALIFICATIONS
Other equivalent qualifications recognised by the Ministry of Higher Education (MOHE) or Malaysian Government will be considered on a case-by-case basis.

 

Note: 

  • Candidates with a pass in Mathematics at SPM level (or Mathematics equivalent to SPM) and without a Mathematics subject in their admission qualification need to take and pass the reinforcement Mathematics subject that is equivalent to the SPM level. The reinforcement Mathematics subject must be offered in the first semester or before enrolment with an unconditional offer. 
  • Candidates with a credit in Computing-related subject(s) at the SPM level (or equivalent to SPM level) may be given preferential consideration. 

Curriculum

  • Computer Organisation and Architecture
  • Fundamentals of Database
  • Discrete Mathematics
  • Calculus and Algebra
  • Data Communications and Networking
  • Computers and Operating Systems
  • Programming with Python
  • Systems Analysis and Design
  • Statistics**
  • Cybersecurity
  • Professionalism and Ethics in Computing
  • Design Thinking
  • Human Computer Interaction
  • Project Management
  • Data Structure and Algorithms
  • Mobile Computing
  • Web Computing
  • Object-Oriented Development
  • Cloud Computing
  • Industrial Training
  • Capstone Project
  • Fundamentals of Data Science**
  • Data Processing and Visualisation**
  • Introduction to Data Mining**
  • Machine Learning**
  • Big Data Architecture