Bachelor in Software Engineering (Honours) (Application Development)

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Digital economy is transforming business models and creating a demand for professionals skilled in helping businesses grow through technology adoption. Industry 4.0 continues to ramp up the demand for software engineering skills to address business challenges and help bridge significant digital skills gap through workforce upskilling.

This programme aims to produce graduates who are skilled in the latest technologies and possess in-depth practical experiences in designing, developing and solving wide-ranging applications and system integration.

Students will learn programming and technical skills, software development processes, web and database development, and software testing and reengineering. These will empower them to handle real-world problems and business environment projects.

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‚ÄúThe expert in anything was once a beginner.‚ÄĚ
Helen Hayes

Top Core Courses

Fundamentals that will build you up to stay relevant and excellent today, tomorrow and beyond.

Data and AI Essentials

Students will be introduced to AI, Data Science and Machine learning, followed by exploratory data analysis which focuses on data statistics, extracting data, cleaning data and transforming data. Then they will be acquainted with machine learning and AI models.

Machine Learning

Students will be taught how to create and evaluate a model in scikit learn and Azure Machine Learning and manage imbalanced data by improving the models. Subsequently, they will be introduced to the application of classification in text analytics.

Deep Learning

Students will comprehend an intuitive approach to build complex models through deep learning with uncompromised scaling, speed, and accuracy. These help machines solve real-world classification text analytics problems and time series problems with human-like intelligence using CNN, RNN and LSTM.

Statistics for Data Science and AI

Students will be introduced to statistical methods such as linear equations, systems of equations, quadratic equations, polynomials, derivatives and multivariate functions. They will develop visualisations using vectors, matrices eigenvectors and eigen values and apply statistics fundamentals, probability, sampling distributions and hypothesis testing in Data Science and AI scenarios.

R Programming

Students will learn R syntax and how to handle data structures consisting of vectors, matrices, factors, data frames and lists. They will build visualisations using the graphical capabilities of R.

Learning Path

Students will obtain all the fundamentals in the field of Software Engineering that will furnish them with the skills required in the industry, such as developing an application and website by integrating the database and other applications together.

Students will begin their internship from this year onwards to enhance professional development and prepare them for their future career path. In addition, they will gain intermediate knowledge about Software Engineering and the best practices to design, develop, and test the software.

Students will be equipped with specialisation skills connected to Industrial Revolution 4.0 such as Machine Learning, Artificial Intelligence, Data Science and Software Engineering.

Students will continue to learn specialisation skills related to Industrial Revolution 4.0 and undergo Industrial Training.

Students will demonstrate their skills and knowledge in the Final Year Project prior to graduation.

Upon graduation, students can embark on careers such as:

  • Software Developer
  • Technical Lead
  • Solutions Architect
  • Cloud Engineer
  • Cloud Architect
  • DecOps Engineer
  • Product Manager
  • UX / UI Developer
  • Scrum Master
  • Automation QA


No.Course CodeCourse TitleCredit Hours
1MPU3213/03Bahasa Kebangsaan A, OR3
MPU3223/03Decision Making Skills
3MPU3313/03Comparative Religions, OR3
MPU3333/03Human Rights
4MPU3113/03Hubungan Etnik OR3
MPU3143/03Bahasa Komunikasi 2
5MPU3123/03Tamadun Islam dan Tamadun Asia3
MPU31273/03Malaysia Studies 3
Subtotal Credit Hours14
1DSE101/03Programming Foundations3
2DSE102/03Front-end Web Development3
3DSE103/03UI Frameworks3
4DSE105/03Web Development Foundations3
5DSE104/03Database Design and Implementation3
6DSE201/03Web Development Using Platforms3
7DSE203/03Develop Enterprise Applications3
8DSE204/03Application Integration3
9DSE205/03Application Development & Processes3
10DSE208/03Agile Apps Development3
11TCC243/03Data Communication and Networking3
12TCC301/03System Security3
13DSE115/03Capstone Project -Web Development3
14DSE211/03Capstone Project ‚Äď Application Development3
15TCC235/03Software Engineering3
16TCC223/03Ethics and Professionlism in Computing3
17TSE313/03Systems Analysis and Design3
18TSE304/03Software Scalability and Reengineering3
19TSE305/03Software Project Management3
20TSE310/03Software Assurance and Quality Assurance3
21TCC122/03Discrete Structures3
Subtotal Credit Hours63
ELECTIVES (Choose ANY FIVE (5) Courses)
1DSE 221/03Data and AI Essentials3
2DSE 222/03Statistics for Data Science and AI3
3DSE 223/03R Programming3
4DSE 242/03Machine Learning3
5DSE 243/03Deep Learning3
6DSE 244/03Reinforcement Learning3
7TSE 307/03Computational Logic3
8TCC 125/03Software Development Models3
9TCC 239/03Data Structures and Algorithms3
Subtotal Credit Hours15
1TUC209/06Industrial Training6
Subtotal Credit Hours6
1DSE309/04Final Project I4
2DSE399/04Final Project II4
Subtotal Credit Hours8
1DSM201/04Creative and Problem Solving4
2DSM218/04Collaborating & Working with Others4
4DBC101/03Business Communication Skills3
Subtotal Credit Hours14
Programme Total Credit Hours120


(A) Regular Entry

Academic Qualification:

  • Matriculation / Foundation

With a minimal CGPA of 2.00 and a credit in Additional Mathematic at SPM level; OR credit in Mathematic and any Science/Technology/Engineering subject at SPM level.

  • STPM (Science Stream or equivalent)

2Cs or CGPA 2.00 with a Credit in a Mathematic subject and a Credit in a Science or ICT subject.

  • UEC

5 Credits (5Bs) inclusive of a credit in Additional Mathematics

  • Diploma

Diploma in Computer Science or Software Engineering or Information Technology or Information System or
Related Diploma in Science and Technology and pass with with minimum CGPA 2.50.


Mathematics Requirement:

  1. Students MUST have attained a ‚ÄėCREDIT‚Äô in ADDITIONAL MATHEMATICS at SPM/O Levels or equivalent; OR
  2. MUST have attained a CREDIT in MATHEMATICS and a CREDIT in either a SCIENCE, TECHNOLOGY or ENGINEERING subject for SPM/O Levels or equivalent. Students using requirement (2) for admission will need to enrol and pass a supplementary mathematics subject to be taken concurrently in Degree.

Note: Students who do not fulfill either requirements are advised to seek advice from the school before enrolment.


(B) Accreditation of Prior Experiential Learning (APEL)

Accreditation of Prior Experiential Learning (APEL) provides an opportunity for individuals with working experience but lack of formal academic qualifications to pursue their tertiary studies. APEL involves the identification, documentation and assessment of prior experiential learning to determine the extent to which an individual has achieved the desired learning outcomes, for access to a programme of study.

Applicants should comply with the following admission criteria stipulated by the Ministry of Higher Education (MOHE) and Malaysian Qualifications Agency (MQA):

  • The candidate should be at least 21 years of age in the year of application and possess relevant work experience.
  • Other equivalent qualifications recognised by the Malaysian Government.

Fee Schedule for the School of Digital Technology (DiGiT)

(Effective May 2022 Semester)


Wawasan Open university uses a unique model of delivering education to Open Distance Learning (ODL) students with tuition fees for the following level of programme that can be worked out as follows:


Total Number of Courses

Total Number of Credits

Tuition Fees (RM)



Bachelor’s Degree

42 ‚Äď 45


70,600 ‚Äď 82,800



  • A one-off payment Processing and Administration fee of RM350 is chargeable for new students.
  • Open Distance Learning Study Resource and Services fee is chargeable every semester and varies according programme.¬† ¬† ¬† ¬† ¬† ¬† ¬†
  • All totals are merely indicative and fees are subject to change without notice.

All of the University’s courses are classified into three categories, i.e., lower level, middle level or higher level. Lower-level courses are basic, introductory or foundation courses designed for freshmen. Middle-level courses may require some knowledge of previous study or a certain amount of intellectual maturity. Higher level courses are specialised courses usually designed for those majoring in a particular discipline. The level of a course is indicated by the first digit of the course code, i.e., lower level courses are indicated by the code 1XX/XX, middle level courses by 2XX/XX and higher level courses by 3XX/XX or 4XX/XX. The 2 digits after the slash indicate the credit value of the course. i.e., WLA101/03 is a lower level course of 3 credits while BBM203/05 is a middle level course of 5 credits and TEC305/10 is a higher level course of 10 credits.

Please click on the below links to download the courses:

+ School of Digital Technology

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