This programme is specifically designed to provide students with:

• The ability to develop technical knowledge, skills and background in the design and organisation of computer systems with an emphasis on data analytics.
• The ability to critically evaluate design paradigms, languages, algorithms, and techniques used to develop complex software systems.
• The ability to evaluate and respond to opportunities for developing and exploiting new technologies with data analytics concepts and tools.

APU and SAS have signed an MoA in partnership to develop Data Scientists in Malaysia. SAS also has endorsed the UG and PG level programmes in Data Analytics by providing tools and educational material support for learning and research purposes. All UG and PG Data Analytics graduates will received a Joint Professional Certificate from SAS.

Graduates will be equipped with knowledge, skills and experience in three major dimensions: Strategic and Commercial applicatio, "hands-on" ICT skills and Statistics & Analytics. The programme is not merely analytics-oriented, but develops  the ability to use analytics to drive key success metrics related t yield management and revenue generation in practically any business domain. There is a tremendous requirement for Data Scientists and Big Data Specialists worldwide now and in the future, with hundreds of thousands of new job opportunities emerging globally. In Malaysia alone, by the year 2020 this need is expected to reach atleast 15,000 professionals.

The programme has been carefully designed by APU with inputs and contents from our partners, compirisng major technology and software solutions providers, university partners as well as industry organisations who use analytics for strategic and competitive advantage.

The strength of these partnerships endures that the programme comprehensively addresses all key stakeholders - Technology providers, Employers, Government as well as Students - in its learning outcomes, curriculum content, delivery adn assessment. Students also obtain certiifcation jointly issued with industry partners, which would certainly give them a head start in the exciting world of Big Data.

Furthermore, APU is also poised to become a frontrunner in analytics research through the establishment of the Asia Pacific Centre of Analytics (APCA), through which research activities will be undertaken to challenge boundaries in the application of analytics.

DEGREE LEVEL 1

Students will learn fundamental skills required by every IT professional, and the basic understanding of programming, mathematical and algorithmic skills. Some specialised modules will provide them basic knowledge of underlying computer systems such as computer architecture, operating systems, networking and databases. The modules will also help them develop personal and organisational skills, as well as nurture creativity and innovation.

Common Modules

• Computing & IT in the Workplace
• Introduction to Management
• System Analysis & Design
• Fundamentals of Software Development
• Mathematical Concepts for Computing
• Operating Systems & Computer Architecture
• Introduction to Networking
• Introduction to Databases

Specialized Modules

• Fundamentals of Artificial Intelligence
• Introduction to C Programming

DEGREE LEVEL 2

A broader range of skills will be learnt, in which students will gain better understanding of designing and implementing new software, and solving new computing problems through theoretical and algorithmic foundations. They will gain solid understanding of platform technology and data analytics through modules in application development and knowledge discovery techniques. We will further nurture their creativity and innovation as well as independent learning to prepare them for the workplace.

Common Modules

• Object Oriented Development with Java
• System Development Methods
• Programming for Data Analysis
• Creativity & Innovation
• Research Methods for Computing and Technology

Specialized Modules

• Computing Theory
• Data Structures
• Concurrent Programming
• Data Management
• Business Intelligence Systems
• Data Mining and Predictive Modelling
• Probability & Statistical Modelling

INTERNSHIP (16 weeks)

After the completion of Level 2 students will undertake a short Internship / Industrial Training. This will prepare them for a smooth transition from the classroom to the world of Computer Science.

DEGREE LEVEL 3

Students will make use of their previous studies and industrial experience to extend their familiarity in the field of computer science and to refine their personal and professional development. Students will move further into the focus on advanced analytics through business analytics and intelligence modules. A final year project requires them to investigate and develop a solution for a real-world problem – they will demonstrate their ability to combine technical knowledge, critical thinking and analytical skills to produce a personal achievement portfolio.

Common Modules

• Innovation Management & New Product Development
• Project Management

Specialized Modules

• Algorithmics
• Real-Time Systems
• Behavioural Science and Marketing Analytics
• Text Analytics and Sentiment Analysis
• Emergent Technology
• Optimisation and Deep Learning
• Database Security
• Investigations in Data Analytics
• Data Analytics Project

MQA Compulsory Subjects*

• Ethnic Relations (M’sian Students)
• Islamic & Asian Civilisation (M’sian Students)
• Malaysian Studies (Int’l Students)
• Malay Communication Language (Int’l Students)
• Workplace Professional Communication Skills
• Employee & Employment Trends
• Co-Curriculum

(*All students are required to successfully complete these modules as stipulated by the Malaysian Qualification Agency)

DIRECT ENTRY TO LEVEL 1 OF THE DEGREE:

STPM         

• 2 Passes in STPM in Science stream with minimum Grade C (GPA 2.0) in Mathematics and one Science or ICT Subject.

• 2 Passes in STPM with minimum Grade C (GPA 2.0) in any subject with a credit in Additional Mathematics at SPM.

• 2 Passes in STPM with minimum Grade C (GPA 2.0) in any subject with a credit in Mathematics and any one Science or ICT subjects at SPM. Candidates need to do a Pre-Requisite module in Further Mathematics or equivalent in the first semester of Degree Programme.

A-LEVEL

• 2 Passes in A-Level in Science stream with a Pass in Mathematics and one Science or ICT subject.

• 2 Passes in A-Level with a Credit in Additional Mathematics at SPM/ IGCSE/ O-Level or equivalent.

• 2 Passes in A-Level with a Credit in Mathematics and Science or ICT subjects at SPM/ IGCSE/ O-Level or equivalent. Candidates need to do a Pre-Requisite module in Further Mathematics or equivalent in the first semester of Degree Programme.

UEC

• 5 Grade B Passes in UEC in any subject including Mathematics and one Science or ICT subject.

• 5 Grade B Passes in UEC in any subject including Additional Mathematics.

• 5 Grade B Passes in UEC in any subjects including Mathematics. Candidates need to do a Pre-Requisite module in Further Mathematics or equivalent in the first semester of Degree Programme.

FOUNDATION/ MATRICULATION

• A pass in Matriculation or Foundation studies with minimum CGPA of 2.0 with a Credit in Additional Mathematics at SPM/ IGCSE/ O-Level or its equivalent.

Note : The requirement for the Additional Mathematics can be exempted if the Matriculation or Foundation offers Mathematics module which is equivalent or higher requirement than the Additional Mathematics at SPM level.

OR

• A pass in Matriculation or Foundation studies with minimum CGPA of 2.0 and a Credit in Mathematics and Science or ICT subject at SPM/ IGCSE/ O-Level or its equivalent. Candidates need to do a Pre-Requisite module in Further Mathematics or equivalent in the first semester of Degree Programme.

Direct Entry to level 2 of the Degree:

• ICT related Diploma with a minimum CGPA of 2.50.

Note: Student with CGPA above 2.0 and below 2.5 may be accepted using rigorous assessment conducted by APU and subject to the approval of the Academic Board.

March, June, Sept, Nov

• Software Tool Developer
• Data Analyst
• Data Scientist
• Data Wrangler/Munger/Miner
• Chief Technology Officer (CTO)
• Data Analytics Manager
• Business Process Engineer
• Machine Learning Scientist
• Analytics Manager
• Business Analyst Manager
• Data Innovation Manager
• Business Intelligence Developer
• IT Risk Analyst
• Advance Analytics Professional
• Data Engineer
• Business Intelligence Analyst
• Business Intelligence Solutions Architect
• Data Visualization Developer