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With data becoming pervasive in the way we live and do business, companies are investing in data analytics capabilities to keep up with developments and competition. However, data analytics tools are evolving at a rapid pace and there is a shortage of qualified data analysts and data scientists in the market today.
To align students with emerging employment trends, the College of Science (CoS) and College of Engineering (CoE) jointly offer the Second Major in Data Analytics. Engineering and Science students can take advantage of their technical knowledge and training in their majors to integrate applications in data analytics. This will expand their career options after graduation and ramp up their employability.
Candidates must meet the minimum entry requirements of the respective Bachelor of Engineering programme, including the minimum subject requirements. Please refer to the Office of Admissions for more information.
Admission enquiries for local students:
Tel: (65) 6790 5055 or (65) 6790 5972
Email: [email protected]
Admission enquiries for international students:
Tel: (65) 6790 5806 or 6790 5807
Email: [email protected]
The structure of the Bachelor of Engineering / Science with a Second Major in Data Analytics (DA) integrates the requirements of both majors, with between 6 - 12AU of double-counting, within the typical candidature of 4 years. Incorporating relevant courses across different schools to provide students with the foundation and practical tools for data analytics, the DA curriculum has been curated to ensure that students receive critical knowledge and skills in the following areas:
(A) Foundation in Mathematics, Statistics and Algorithms: The core courses in this group are focused on probability and statistics, linear algebra and algorithms/programming. It is essential that every data analyst or data scientist understands the theoretical underpinnings in order to be able to build reliable models with real-world applications.
(B) Essentials in Data Analytics: The core courses in this group are focused on database, data mining and data visualization/management. These courses aim to prepare students for key responsibilities of a data analyst which generally include designing and maintaining data systems and databases, mining data from primary and secondary sources, using statistical tools to interpret data for diagnostic and predictions, and visualization tools for reporting and communications.
(C) Advanced Electives in Data Analytics: With a variety of elective courses across different schools in COS and COE, students are able to gain in-depth exposure to artificial intelligence, neural network, machine learning, natural language processing and higher-level courses in statistics, computations and algorithms.
For more information on the programme structure, you may refer here.
Click here for more information on our curriculum.
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