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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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Bachelor of Information Technology (Honours) (Data Analytics)

Course overview

Statistics
Qualification Bachelor's Degree
Study mode Full-time
Duration 3 years
Intakes March, July, November
Tuition (Local students) $ 7,000
Tuition (Foreign students) $ 9,000

About

The Bachelor of Information Technology (Honours) (Data Analytics) program focuses on enhancing analytical skills within the field of Information Technology. The program offers a core of Information Technology modules along with a selection from various courses covering the latest advances in IT skills, concepts, and applications. These include Parallel Programming, Information Systems Analysis and Design, Web and Network Analytics, Knowledge Management, and Data Visualization.

Admissions

Intakes

Fees

Tuition

$ 7,000
Local students
$ 9,000
Foreign students

Estimated cost as reported by the Institution.

Application

Data not available
Local students
$ 181
Foreign students

Student Visa

$ 544
Foreign students

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.

Entry Requirements

i. Passed Sijil Tinggi Persekolahan Malaysia (STPM) with a full pass in 2 subjects or equivalent with a minimum CGPA of 2.0 and pass the Sijil Pelajaran Malaysia (SPM) or equivalent with a credit in Mathematics; or

ii. Passed the Matriculation Programme or Foundation of PPT recognized by the Malaysian Government with a CGPA of 2.0 and credit in Mathematics at SPM level or equivalent; or

iii. A Diploma [Level 4, Malaysian Qualifications Framework (MQF)] in Computer Science or Software Engineering or Information Technology or Information Systems or equivalent with a minimum 2.50 and a credit in Mathematics at SPM level or its equivalent;

iv. Any other Diploma (Level 4, MQF) in Science and Technology or Business Studies with a minimum CGPA of 2.50 may be admitted, subject to a rigorous internal assessment process and a credit in Mathematics at SPM level or its equivalent;

v. Other equivalent qualifications recognized by the Malaysian Government.

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.

Candidate with a credit in Computing related subject at SPM or STPM level or its equivalent mat be given preferential consideration.

Curriculum

  • - Principles of Programming
  • - Discrete Mathematics and Probability
  • - English
  • - Islamic Civilization and Asian Civilization / Malay Language Communication
  • - Computer Architecture and Organisation
  • - Ethnic Relations / Malaysian Studies
  • - Computer Networks
  • - Database Management Systems
  • - Applied Statistics
  • - Object-Oriented Programming
  • - Malaysian Government and Public Policy
  • - Data Structures and Algorithms
  • - Information Systems Analysis and Design
  • - Information Systems Security
  • - Values & Ethics in Profession
  • - Data Science Principles
  • - Python for Data Analytics
  • - Enterprise Architecture
  • - Human-Computer Interaction
  • - Social Media Analytics
  • - Web Analytics and Intelligence
  • - Big Data Analytics
  • - Project Management
  • - Leadership Skills and Human Relations
  • - Parallel Computing
  • - Text Analytics and Sentiment Analysis
  • - Organizational Behavior
  • - Business Intelligence Systems
  • - Optimization for Data Analytics
  • - Final Year Project
  • - Industrial Training
  • - Predictive Analytics and Business Forecasting
  • - Data Visualization

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