The Second Major in Data Analytics equips Environmental Engineering students with additional technical competency to integrate applications with data analytics.
With data becoming pervasive in the way we live, 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.
Environmental Engineering students can take advantage of their technical knowledge and training in the environmental domain to integrate applications in data analytics. This will expand their career options after graduation.
- 4 years direct honours programme
- Accredited and globally recognised programme
- 20 weeks Professional Internship
Students with outstanding Singapore GCE ‘A’ Level, International Baccalaureate (IB) and NUS High School Diploma results may be eligible for exemptions from up to 3 selected first-year courses, more details could be found via the following link
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.
- Professional Internship: Curriculum Structure | Course Content
- Professional Attachment: Curriculum Structure | Course Content
Second Major in Data Analytics constitutes a total of 30 - 38AU, including 21 - 26AU of Compulsory Courses covering 7 key knowledge areas, as well as 9 - 12AU of data-related electives. Table 1 below shows the course options offered in each Knowledge Area as well as the electives that students can choose from. Some courses in Knowledge Areas 1 - 4 are Core or Major Prescribed Elective (MPE) in the respective primary Bachelor of Engineering/Science programme and can therefore be double-counted towards both majors. Please select your programme in Programme Options above to access the recommended courses and study plan.
Table 1: Courses and AU Requirements for the Second Major in Data Analytics
KNOWLEDGE AREA | COURSES | AU |
COMPULSORY (1 course required in each knowledge area) | ||
1) Probability and Statistics |
| 3 |
2) Linear Algebra |
| 3 |
3) Data Analysis / Computing |
| 3 |
4) Algorithms |
| 3 |
5) Database |
| 3 - 4 |
6) Data Mining |
| 3 - 4 |
7) Data Visualisation / Management |
| 3 - 4 |
Total AU for Compulsory Courses | 21 - 24 | |
ELECTIVES (Minimum 9AU) | ||
• BC2407 Analytics II: Advanced Predictive Techniques* (4AU) • BS3008 Computational Biology and Modeling* (3AU) • BS4017 High-Throughput Bioinformatics* (3AU) • CM4043 Molecular Modelling: Principles and Applications* (3AU) • CM4044 Artificial Intelligence in Chemistry* (3AU) • ES2001 Computational Earth Systems Science* (4AU) • MH3400 Algorithms for the Real World* (4AU) @ • MH3500 Statistics* (4AU) @ • MH3510 Regression Analysis* (4AU) @ • MH3511 Data Analysis with Computer* (3AU) @ • MH3701 Basic Optimization* (4AU) • MH4500 Time Series Analysis* (4AU) @ • MH4513 Survival Analysis* (4AU) @ • MH4302 Theory of Computing* (4AU) • MH4320 Computational Economics* (4AU) @ • MH4511 Sampling and Survey* (4AU) @ • MH4512 Clinical Trials* (4AU) • MH4702 Probabilistic Methods in OR* (4AU) @ • CH4244 Numerical Method and Data Analytics* (3AU) • EE4414 Machine Learning Design & Application* (3AU) • EE4497 Pattern Recognition & Machine Learning (3AU) • MA4829 Machine Intelligence (3AU) • MA4830 Real Time Software for Mechatronics System (3AU) • MA4832 Microprocessor System (3AU) • MS4671 Introduction to Materials Simulation (3AU) • SC3020 Database System Principle* (3AU) • SC4001 Neural Network and Deep Learning* (3AU) • SC4002 Natural Language Processing* (3AU) • SC4021 Information Retrieval* (3AU) • SC4022 Network Science* (3AU) | 9 - 12 | |
Total AU for Second Major | 30 - 38 | |
* Pre-requisites apply |
The Second Major in Data Analytics will open up a broad and diverse range of career prospects including:
- Data Scientist
- Research Scientist
- R&D Engineer
- Business Intelligence Developer
- Data Analyst
- Data Architect
Related Programmes
- Double Degree in Bachelor of Engineering in Environmental Engineering and Bachelor of Social Science in Economics
- Bachelor of Engineering in Environmental Engineering with Second Major in Business
- Bachelor of Engineering in Environmental Engineering with a Second Major in Entrepreneurship
- Bachelor of Engineering in Environmental Engineering with Second Major in Society & Urban Systems
- Bachelor of Engineering in Environmental Engineering