Last modified: 07 Aug 2025 12:16
This course introduces computational methods in Physics and Astrophysics. It consists of an introduction to programming, starting at basics such as variables, loops and conditional statements. This course is taught in Python, with an emphasis on modern programming concepts and data analysis skills.
| Study Type | Undergraduate | Level | 2 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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This course will introduce computing skills including programming and numerical analysis methods. Students will develop programming and numerical analysis skills. Using Python, they will first learn the basics of programming, including loops, conditions and functions. Using this basis, they will then apply numerical algorithms to solve differential equations, eigenvalue problems and integration, and learn how to analyse and visualise data. An individual programming project on the numerical simulation of planetary motion concludes the course.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 40 | |
|---|---|---|---|---|
| Assessment Weeks | 11,12,13,14,15,16,17 | Feedback Weeks | 12,13,14,15,16,17,18 | |
| Feedback |
7 equally weighted Tutorial Sheets worth in total 40% of the course grade. The tutorial sheets comprise questions that require the application of Python coding techniques covered in lectures. Written feedback via MyAberdeen. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Understand numerical methods to address problems involving linear algebra, random numbers and numerical integration. |
| Procedural | Apply | Be familiar with SciPy and Pandas scientific libraries for statistics and data analysis and be able to apply them. |
| Procedural | Apply | Understand and implement basic programming concepts: algorithms, loops, conditional statements, functions, etc. |
| Procedural | Apply | Be able to use scientific libraries for scientific computations and plotting. |
| Assessment Type | Summative | Weighting | 60 | |
|---|---|---|---|---|
| Assessment Weeks | 19 | Feedback Weeks | 21 | |
| Feedback |
Design Project worth 60% of the overall grade. Students will simulate a physical system using Python. The project is structured around a series of guided, incremental tasks that lead step by step toward a complete implementation. Written feedback via MyAberdeen. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Understand numerical methods to address problems involving linear algebra, random numbers and numerical integration. |
| Procedural | Apply | Understand and implement basic programming concepts: algorithms, loops, conditional statements, functions, etc. |
| Procedural | Apply | Be able to use scientific libraries for scientific computations and plotting. |
| Procedural | Apply | Be familiar with SciPy and Pandas scientific libraries for statistics and data analysis and be able to apply them. |
| Procedural | Create | Create and develop a mathematical programming project. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
2-hour resit exam. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | Be familiar with SciPy and Pandas scientific libraries for statistics and data analysis and be able to apply them. |
| Procedural | Apply | Be able to use scientific libraries for scientific computations and plotting. |
| Procedural | Apply | Understand and implement basic programming concepts: algorithms, loops, conditional statements, functions, etc. |
| Procedural | Create | Create and develop a mathematical programming project. |
| Conceptual | Understand | Understand numerical methods to address problems involving linear algebra, random numbers and numerical integration. |
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