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MADA (Matric Yr 2022-2023)
BSc in Mathematical Sciences with Second Major in Data Analytics
Curriculum (Matriculation Year 2022-2023)
Curriculum Overview
The Mathematical Sciences major is divided into four tracks: Pure Mathematics (PMAS), Applied Mathematics (AMAS), Statistics (STAT), and Business Analytics (BA). The distribution of Academic Units (AU) varies between the different tracks.
| Course Type | Academic Units (AU) | |||
|---|---|---|---|---|
| PMAS | AMAS | STAT | BA | |
| Core Courses | 45 | 45 | 45 | 37 |
| Track Core | 7 | 7 | 8 | 13 |
| Prescribed Electives for chosen Track Choose one of the two options: AU figures for the PI option are shown in parentheses. | 24 (19) | 24 (19) | 23 (18) | 26 (21) |
| Second Major Courses: | 21 | |||
| Interdisciplinary Collaborative Core: Common Core | 17 | |||
| Interdisciplinary Collaborative Core: Foundational Core | 10 (15) | |||
| Broadening and Deepening Electives (BDE) Can take BDEs offered by any School. | 12 | |||
| Total | 136 AU | |||
Notes:
- AU figures in parentheses (x) indicate the number of AU if the option with PI is selected.
- A grade of A- or better in the Final Year Project (MH4900) is required to be eligible for Honours (Highest Distinction).
- Students who do not take the Final Year Project can opt to do either Professional Internship (MH4912) or Professional Attachment (MH4913).
- To satisfy the major with a Concentration in the Mathematics of Information and Communication, a student must also pass four courses in the Mathematics of Information and Communication List.
- To satisfy the major with a Concentration in Computational Mathematics, a student must also pass four courses in the Computational Mathematics List.
Curriculum by Year
Year 1 Semester 1
| MH1100 - Calculus I | 4 AU |
| MH1200 - Linear Algebra I | 4 AU |
| MH1300 - Foundations of Mathematics | 4 AU |
| PS0001 - Introduction to Computational Thinking | 3 AU |
| CC0003 - Ethics & Civics in a Multi-Cultural World | 2 AU |
| CC0002 - Navigating the Digital World | 2 AU |
| HW0001 - Introduction to Academic Communication (for students who fail QET) | 0 AU |
Year 1 Semester 2
| MH1101 - Calculus II | 4 AU |
| MH1201 - Linear Algebra II | 4 AU |
| MH1301 - Discrete Mathematics | 3 AU |
| MH1403 - Algorithms and Computing | 3 AU |
| CC0001 - Inquiry and Communication in an interdisciplinary World | 2 AU |
| CC0005 - Healthy Living and Wellbeing | 3 AU |
Year 2 Semester 1
| MH2100 - Calculus III | 4 AU |
| MH2500 - Probability and Introduction to Statistics | 4 AU |
| CC0006 - Sustainability: Society, Economy & Environment | 3 AU |
| ML0004 - Career and Entrepreneurial Development for the Future World | 2 AU |
| Broadening and Deepening Elective(s) / Second Major course(s) | 3/4 AU each |
| For Pure Mathematics Track (PMAS) | |
|---|---|
| MH2220 - Algebra I | 3 AU |
| For Business Analytics Track (BA) | |
| BE1402 - Business Operations and Processes | 3 AU |
| BU8601 - Fundamentals of Management | 3 AU |
Year 2 Semester 2
| PS0002 - Introduction to Data Science and Artificial Intelligence | 3 AU |
| CC0007 - Science & Technology for Humanity | 3 AU |
| Track Prescribed Elective(s) | 4 AU each |
| Broadening and Deepening Elective(s) / Second Major course(s) | 3/4 AU each |
| For Pure Mathematics Track (PMAS) | |
|---|---|
| MH3100 - Real Analysis I | 4 AU |
| MH3110 - Ordinary Differential Equations | 4 AU |
| For Applied Mathematics Track (AMAS) | |
| MH3100 - Real Analysis I | 4 AU |
| MH3110 - Ordinary Differential Equations | 4 AU |
| MH3701 - Basic Optimization | 4 AU |
| For Statistics Track (STAT) | |
| MH3100 - Real Analysis I | 4 AU |
| MH3110 - Ordinary Differential Equations | 4 AU |
| MH3500 - Statistics | 4 AU |
| For Business Analytics Track (BA) | |
| MH3500 - Statistics | 4 AU |
| MH3511 - Data Analysis with Computer | 3 AU |
Year 2 Special Terms
| MH4913 Professional Attachment (for PA option; can also be taken during Year 3 Special Terms) | 5 AU |
Year 3 Semester 1
| HW0218 - Communication Across the Sciences | 2 AU |
| Track Prescribed Elective(s) | 4 AU each |
| Broadening and Deepening Elective(s) / Second Major course(s) | 3/4 AU each |
| For Pure Mathematics Track (PMAS) | |
|---|---|
| MH3101 - Complex Analysis | 4 AU |
| For Statistics Track (STAT) | |
| MH3510 - Regression Analysis | 4 AU |
Year 3 Semester 2
| Track Prescribed Elective(s) | 4 AU each |
| Broadening and Deepening Elective(s) / Second Major course(s) | 3/4 AU each |
| For Applied Mathematics Track (AMAS) | |
|---|---|
| MH3700 - Numerical Analysis I | 3 AU |
Year 3 Special Terms
| MH4913 Professional Attachment (for PA option; can also be taken during Year 2 Special Terms) | 5 AU |
Year 4 Semester 1
| Track Prescribed Elective(s) | 4 AU each |
| Broadening and Deepening Elective(s) / Second Major course(s) | 3/4 AU each |
| MH4912 - Professional Internship (for PI option) | 10 AU |
Year 4 Semester 2
| Track Prescribed Elective(s) | 4 AU each |
| Broadening and Deepening Elective(s) / Second Major course(s) | 3/4 AU each |
Prescribed Electives
- Option with PA: Choose 24 AU of courses from the following list; at least 16 AU must be level 4 or higher.
- Option with PI: Choose 19 AU of courses from the following list; at least 8 AU must be level 4 or higher (excluding the Final Year Project (MH4900)).
| MH3220 - Algebra II | 4 AU | Sem 1 |
| MH3210 - Number Theory | 4 AU | Sem 1 |
| MH3400 - Algorithms for the Real World | 4 AU | Sem 2 |
| MH3520 - Mathematics of Deep Learning | 4 AU | Sem 1 |
| MH3600 - Topology and Manifolds | 4 AU | Sem 2 |
| MH4100 - Real Analysis II | 4 AU | Sem 2 |
| MH4200 - Abstract Algebra II | 4 AU | Sem 2 |
| MH4300 - Combinatorics | 4 AU | Sem 1 |
| MH4301 - Set Theory and Logic | 4 AU | Sem 1 or 2 |
| MH4302 - Theory of Computing | 4 AU | Sem 1 or 2 |
| MH4310 - Coding Theory | 4 AU | Sem 2 |
| MH4311 - Cryptography | 4 AU | Sem 1 |
| MH4600 - Algebraic Topology | 4 AU | Sem 2 |
| MH4601 - Differential Geometry | 4 AU | Sem 2 |
| MH7002 - Discrete Methods | 4 AU | Sem 2 |
| MH4900 - Final Year Project | 8 AU | Sem 1 & 2 |
| MH4910, MH4911, MH492x, MH493x (subject to division approval) | 4 AU |
- Option with PA: Choose 24 AU of courses from the following list; at least 16 AU must be level 4 or higher.
- Option with PI: Choose 19 AU of courses from the following list; at least 8 AU must be level 4 or higher (excluding the Final Year Project (MH4900)).
| MH2220 - Algebra I | 3 AU | Sem 2 |
| MH3101 - Complex Analysis | 4 AU | Sem 1 |
| MH3300 - Graph Theory | 4 AU | Sem 1 |
| MH3400 - Algorithms for the Real World | 4 AU | Sem 2 |
| MH3512 - Stochastic Processes | 4 AU | Sem 1 |
| MH3520 - Mathematics of Deep Learning | 4 AU | Sem 1 |
| MH3600 - Topology and Manifolds | 4 AU | Sem 2 |
| MH4110 - Partial Differential Equations | 4 AU | Sem 2 |
| MH4302 - Theory of Computing | 4 AU | Sem 1 or 2 |
| MH4310 - Coding Theory | 4 AU | Sem 2 |
| MH4311 - Cryptography | 4 AU | Sem 1 |
| MH4320 - Computational Economics | 4 AU | Sem 1 |
| MH4514 - Financial Mathematics | 4 AU | Sem 2 |
| MH4517 - Data Applications in Natural Sciences | 4 AU | Sem 2 |
| MH4518 - Simulation Techniques in Finance | 4 AU | |
| MH4700 - Numerical Analysis II | 4 AU | Sem 1 |
| MH4701 - Mathematical Programming | 4 AU | Sem 1 |
| MH4702 - Probabilistic Methods in OR | 4 AU | Sem 1 |
| MH7002 - Discrete Methods | 4 AU | Sem 1 |
| SC2001 - Algorithm Design and Analysis | 3 AU | |
| SC4001 - Neural Network and Deep Learning | 3 AU | |
| EE4476 - Image Processing | 3 AU | |
| MH4900 - Final Year Project | 8 AU | Sem 1 & 2 |
| MH4910, MH4911, MH492x, MH493x (subject to division approval) | 4 AU |
- Option with PA: Choose 23 AU of courses from the following list; at least 15 AU must be level 4 or higher.
- Option with PI: Choose 18 AU of courses from the following list; at least 7 AU must be level 4 or higher (excluding the Final Year Project (MH4900)).
- Option with PA: Choose 26 AU of courses from the following list. At least 2 courses must be from List B1, and at least 14 AU must be level 4 or higher.
- Option with PI: Choose 21 AU of courses from the following list. At least 2 courses must be from List B1, and at least 6 AU must be level 4 or higher (excluding the Final Year Project (MH4900)).
| List B1 | |
|---|---|
| BC2402 - Designing & Developing Databases | 4 AU |
| BT2404 - Services Operations Management | 3 AU |
| BC3410 - Financial Service Processes and Analytics | 3 AU |
| List B2 | |
| MH3110 - Ordinary Differential Equations | 4 AU |
| MH3400 - Algorithms for the Real World | 4 AU |
| MH3510 - Regression Analysis | 4 AU |
| MH3520 - Mathematics of Deep Learning | 4 AU |
| MH3700 - Numerical Analysis I | 3 AU |
| MH3701 - Basic Optimization | 4 AU |
| MH4320 - Computational Economics | 4 AU |
| MH4500 - Time Series Analysis | 4 AU |
| MH4501 - Multivariate Analysis | 4 AU |
| MH4510 - Statistical Learning and Data Mining | 4 AU |
| MH4513 - Survival Analysis | 4 AU |
| MH4517 - Data Applications in Natural Sciences | 4 AU |
| MH4518 - Simulation Techniques in Finance | 4 AU |
| MH4700 - Numerical Analysis II | 4 AU |
| MH4701 - Mathematical Programming | 4 AU |
| MH4702 - Probabilistic Methods in OR | 4 AU |
| SC2207 - Introduction to Databases | 3 AU |
| SC4000 - Machine Learning | 3 AU |
| SC4021 - Information Retrieval | 3 AU |
| MH4900 - Final Year Project | 8 AU |
| MH4910, MH4911, MH492x, MH493x (subject to approval by division) | 4 AU |
Second Major Courses
Required Second Major Courses
The following courses are double-counted towards both the Major and Second Major requirements:
| MH1201 - Linear Algebra II | 4 AU | Sem 2 |
| MH1403 - Algorithms and Computing | 3 AU | Sem 2 |
| MH2500 - Probability and Introduction to Statistics | 4 AU | Sem 1 |
For students in the Pure Mathematics (PMAS), Applied Mathematics (AMAS), and Statistics (STAT) tracks, the following course must be read:
| MH3511- Data Analysis with Computer | 3 AU | Sem 2 |
Choose one course from each of the following Knowledge Area Lists:
Databases
| BC2402 - Designing & Developing Databases | 4 AU | Sem 1 |
| EE4791 - Database Systems | 3 AU | Sem 2 |
| SC2207 - Introduction to Database* | 3 AU | Sem 1 & 2 |
* Prerequisites apply. Click here for approved prerequisite mappings.
Data Mining
| MH4510 - Statistical Learning & Data Mining* | 4 AU | Sem 1 |
| EE4483 - Artificial Intelligence & Data Mining* | 3 AU | Sem 1 |
| SC4020 - Data Analytics & Mining* | 3 AU | Sem 1 |
* Prerequisites apply. Click here for approved prerequisite mappings.
Data Visualization/Management
| BC2406 - Analytics I: Visual and Predictive Techniques* | 4 AU | Sem 1 |
| SC4023 - Big Data Management* | 3 AU | Sem 2 |
| SC4024 - Data Visualization* | 3 AU | Sem 1 |
* Prerequisites apply. Click here for approved prerequisite mappings.
Second Major Electives
Choose at least 3 courses from the following list. At least 6 AU must be chosen from non MH-coded courses and the total AU for the Second Major must be at least 21 (excluding MH1201, MH1403 and MH2500 which are double-counted).
| MH3400 - Algorithms for the Real World | 4 AU |
| MH3500 - Statistics | 4 AU |
| MH3510 - Regression Analysis | 4 AU |
| MH3701 - Basic Optimization | 4 AU |
| MH4302 - Theory of Computing | 4 AU |
| MH4320 - Computational Economics | 4 AU |
| MH4500 - Time Series Analysis | 4 AU |
| MH4511 - Sampling & Survey | 4 AU |
| MH4512 - Clinical Trials | 4 AU |
| MH4513 - Survival Analysis | 4 AU |
| MH4702 - Probabilistic Methods in OR | 4 AU |
| BC2407 - Analytics II: Advanced Predictive Techniques* | 4 AU |
| BS3008 - Computational Biology and Modelling* | 3 AU |
| BS4017 - High-Throughput Bioinformatics | 3 AU |
| CH4244 - Numerical Method and Data Analytics | 3 AU |
| CM4043 - Molecular Modelling: Principles and Applications | 3 AU |
| CM4044 - Artificial Intelligence in Chemistry | 3 AU |
| EE4414 - Machine Learning Design & Application | 3 AU |
| EE4497 - Pattern Recognition & Machine Learning | 3 AU |
| ES2001 - Computational Earth Systems Science | 4 AU |
| MA4829 - Machine Intelligence | 3 AU |
| MA4830 - Real Time Software for Mechatronics System | 3 AU |
| MA4832 - Microprocessor System | 3 AU |
| MS4671 - Introduction to Materials Simulation | 3 AU |
| SC3020 - Database System Principle | 3 AU |
| SC4001 - Neural Network and Deep Learning | 3 AU |
| SC4002 - Natural Language Processing | 3 AU |
| SC4021 - Information Retrieval | 3 AU |
| SC4022 - Network Science | 3 AU |
Approved Mapping of Prerequisites
| Course | Offering School | Prerequisite(s) | Approved Mapping for MADA |
|---|---|---|---|
| EE4483 | EEE | EE2107/EE/IM2007 + EE0005/EE1005 | MH1201/MH2802 + PS0002 |
| SC2207 | SCSE | SC2001 | MH1403 |
| SC4002 | SCSE | SC2001 | MH1403 |
| SC4020 | SCSE | SC2001 | MH1403 |
| SC4022 | SCSE | SC2001 | MH1403 |
| SC4024 | SCSE | SC1003 + SC2000 | MH2500 + PS0001 |
Special Broadening and Deepening Electives
The following courses are offered specially to MAS students, to be read as Broadening and Deepening Electives.