BSDA Curriculum AY2025 Intake

 

Biological Sciences with 2nd major in Data Analytics Requirements
TypeNo of AU
Major RequirementsCore39
Major Prescribed Electives (PE)33
Interdisciplinary Collaborative CoreCommon Core14
Professional Series16
Care, Serve, Learn3
Broadening and Deepening Electives (BDE)Broadening & Deepening Electives32
Total137

 

BS Core & ICC Core Courses

Year 1
Semester 1
TypeCourse CodeCourse TitleAU
Core BS1012Foundations of Chemistry I 3
CoreBS1016Physiology3
CoreBS1008Biostatistics 3
ICC (Common Core) CC0001

 

Inquiry and Communication in an Interdisciplinary World 2
ICC (Common Core)CC0003Ethics & Civics in a Multi-Cultural World 2
ICC (Common Core)CC0015Health & Wellbeing 2


Year 1
Semester 2
TypeCourse CodeCourse TitleAU
Core  BS1013 Foundations of Chemistry II3
Core BS1005Biochemistry I3
Core  BS1006Principles of Genetics3
Core BS1007Molecular and Cell Biology I3
Core*BS1009* Introduction to Computational Thinking3
CoreBS1100Molecular and Cell Biology Techniques Level 13
ICC (Common Core)ML0004Career Design & Workplace Readiness in the V.U.C.A World  2

 

Year 2
Semester 1
TypeCourse CodeCourse TitleAU
Core BS2002Microbiology
3
Core BS2003Biochemistry II3
Core BS2028Instrumentation for the Analysis of Biological Systems3
ICC (Professional Series)BS0004Introduction to Data Science 3
ICC (Common Core)CC0007Science & Technology for Humanity3

** You may read MH2802 Linear Algebra for Scientists in Year 2 sem 1 or Year 3 sem 1. 

Year 2
Semester 2
TypeCourse CodeCourse TitleAU
Core BS2004Molecular & Cell Biology II3
ICC (Care, Serve, Learn)TBCCare, Serve, Learn (CSL)3
ICC (Common Core)CC0006Sustainability: Society, Economy & Environment3
ICC (Professional Series)HW0218Communication Across the Sciences2


Year 3
Semester 1
TypeCourse CodeCourse TitleAU
ICC (Professional Series) MLxxxxProfession Preparation Course1


Year 3
Semester 2
TypeCourse CodeCourse TitleAU
ICC (Professional Series)BS4227Professional Internship10

 

Major Prescribed Electives

Starting from Year 2 Sem 1 to Year 4 Sem 2 (Semester 1 or 2)TypeCoursesAU
MPE

Table A

33 (21)
Table B

 

 

 

BS4020 Final Year Project or BS4021 Bi-Semestral Final Year Project.                  

Students who opted for BS4020 Final Year Project (full semester) are not allowed to read any course in the particular semester.

Students who opted for BS4021 Bi-Semestral FYP are allowed to read 3 courses (9AU) in each semester. BS4021 Bi-Semestral FYP must start in Year 4 Sem 1. 

 

 

12

AU figures in brackets (x) indicate the number of AU for MPE courses if a Full Semester (BS4020 FYP or BS4021 Bi-Semestral FYP) is selected.

 

Compulsory Second Major in DA Courses

7 COMPULSORY COURSES (1 course in each knowledge area) 
Knowledge AreaCoursesSemester
Probability and StatisticsMH2500 Probability & Introduction to Statistics# (4AU)Sem 1
Linear AlgebraMH2802 Linear Algebra for Scientists (3AU)Sem 1
Data Analysis / ComputingBS1009 Introduction to Computational Thinking (3AU)Sem 2
AlgorithmsMH1403 Algorithms and Computing (3AU)Sem 2
Database (Choose 1)BC2402 Designing & Developing Databases (4AU)Sem 1
EE4791 Database Systems (3AU)Sem 2
SC2207 Introduction to Database* (3AU)
Sem 1 & 2
Data Mining (Choose 1)MH4510 Statistical Learning & Data Mining* (4AU)Sem 1
EE4483 Artificial Intelligence & Data Mining* (3AU)Sem 1
SC4020 Data Analytics and Mining* (3AU)Sem 1
Data Visualisation /
Management (Choose 1)
BC2406 Analytics I: Visual and Predictive Techniques* (4AU)Sem 1
 SC4023 Big Data Management* (3AU)Sem 2
 SC4023 Big Data Management* (3AU)Sem 1
 Total Minimum 22 AUs

# MH1802 (pre-requisite for MH2500), the course will be pre-registered in Y1S1 as free BDE.

* Prerequisites apply. View approved prerequisite mappings below

The following BS course is double-counted towards both Core and Second Major requirements:

BS1009 Introduction to Computational Thinking 3 AU

 

Second Major in DA Electives

Table C (BDE for 2nd major) - To choose at least 3 courses

Minimum 9 AUs

Course Code & Title No. of AU
MH3400 - Algorithms for the Real World* 4
MH3500 - Statistics* 4
MH3510 - Regression Analysis* 4
MH3511 - Data Analysis with Computer* 3
MH3701 - Basic Optimization* 4
MH4302 - Theory of Computing* 4
MH4320 - Computational Economics* 4
MH4500 - Time Series Analysis* 4
MH4511 - Sampling & Survey* 4
MH4512 - Clinical Trials* 4
MH4513 - Survival Analysis* 4
MH4702 - Probabilistic Methods in OR* 4
BC2407 - Analytics II: Advanced Predictive Techniques* 4
BS3008 - Computer Aided Drug Discovery*
BS4017 - High-Throughput Bioinformatics*
CH4244 - Numerical Method and Data Analytics*
CM4043 - Molecular Modelling: Principles and Applications*
CM4044 - Artificial Intelligence in Chemistry*
EE4414 - Machine Learning Design & Application*
EE4497 - Pattern Recognition & Machine Learning
ES2001 - Computational Earth Systems Science*
MA4829 Machine Intelligence 
MA4830 Real Time Software for Mechatronics System
MA4832 Microprocessor System
MS4671 Introduction to Materials Simulation
SC3020 - Database System Principle* 3
SC4001 - Neural Network and Deep Learning*
SC4002 - Natural Language Processing*
SC4021 - Information Retrieval*
SC4022 - Network Science*

* Prerequisites apply. View approved prerequisite mappings below.

The following two elective courses can be used for double-counting towards both Major Prescribed Elective and the Second Major Elective Requirement.

BS3008 Computer Aided Drug Discovery 3 AU
BS4017 High-Throughput Bioinformatics 3 AU

 

Approved Prerequisite Mappings

Course Offering School Prerequisite(s) Approved Mapping for BSDA
Course Offering School Prerequisite(s) Approved Mapping for BSDA
MH1403 SPMS PS0001 BS1009
SC2207 SCSE SC2001 MH1403
SC4002 SCSE SC2001 MH1403
SC4020 SCSE SC2001 MH1403
SC4022 SCSE SC2001 MH1403
SC4024 SCSE SC1003 & SC2000 BS1009 & MH2500

NTU reserves all rights to make changes to the programme structure with prior notice.​​​​​​​​​     

Click here to view outcome-based teaching and learning (OBTL) course information.

Click  here to view the double-Count Policy for BSDA programme.

It is not mandatory to follow the suggested study year. Students can modify this study plan based on their learning needs.

More information on MOOC is at https://www.ntu.edu.sg/admissions/matriculation/mooc

Information is accurate at the time of publication. The University reserves all rights to make changes to the programme structure with prior notice.​​​​​​​​​