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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“The expert in anything was once a beginner.”
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.

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