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PHDA (Matric Yr 2024)
BSc in Physics / Applied Physics
with Second Major in Data Analytics
Curriculum (Matriculation Year 2024)
- Overview
- Core Courses
- Major Prescribed Electives:
- Courses for Second Major in Data Analytics:
- Broadening and Deepening Electives
Curriculum Overview
| Academic Units (AU) | |||
|---|---|---|---|
| Course Type | Option with PA & FYP | Option with PI without FYP | Option with PI & FYP |
| Core Courses | 61 AU (PPHY) 60 AU (APHY) | 61 AU (PPHY) 60 AU (APHY) | 61 AU (PPHY) 60 AU (APHY) |
Prescribed Electives for Physics or Applied Physics Students must take at least 3 AU of PH4XXXX course from the Prescribed Electives courses. |
13 AU | 8 AU | 13 AU |
| Second Major courses | 28 AU | 28 AU | 28 AU |
| Interdisciplinary Collaborative Core: Common Core | 17 AU | 17 AU | 17 AU |
| Interdisciplinary Collaborative Core: Foundational Core | 10 AU | 15 AU | 15 AU |
Broadening and Deepening Electives (BDE) | 12 AU | 12 AU | 7 AU |
| Total | 141 AU (PPHY) 140 AU (APHY) | 141 AU (PPHY) 140 AU (APHY) | 141 AU (PPHY) 140 AU (APHY) |
Notes:
- AU figures in brackets (x) indicates the number of AU if the semester long internship is selected.
- Must read either Final Year Project (PH44XX) or Professional Internship (PH4420).
- A minimum CGPA of 4.50 and a grade of A- or better in the Final Year Project are required to be eligible for Honours (Highest Distinction). A minimum CGPA of 4.00 and a 'Pass' grade in the Final Year Project are required to be eligible for Honours (Distinction).
- All common core and graduate level courses cannot be mapped to exchange courses. PH4XXX courses can only be mapped to exchange courses as BDE, unless the exchange course is a graduate-level course. Please refer to this page for more information.
Core Courses
Prescribed Electives for Physics
Prescribed Electives for Applied Physics (APHY)
Second Major Courses
Required Second Major Courses
The following course is double-counted towards both Major and Second Major requirement:
| MH2802 - Linear Algebra for Scientists | 3 AU | Sem 1 |
The following courses must also be read:
| MH1403 - Algorithms and Computing | 3 AU | Sem 2 |
| MH2500 - Probability and Introduction to Statistics | 4 AU | Sem 1 |
| 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.
Elective Second Major Courses
Choose at least 3 courses from the following list. The total AU for the Second Major must be at least 28 AU (excluding MH2802 which is 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 |
Broadening & Deepening Electives
Students may read any Broadening & Deepening Electives (BDEs) offered by any School in NTU. The following physics-specific BDE may be read by interested students:
| Semester 1 | |
|---|---|
| PH2901 - Electronics for the Experimentalist | 3 AU |
| Special Term | |
| PS5000 - Introduction to Undergraduate Research Experience (for early matriculated and Year 1 students only) | 3 AU |