Last modified: 31 Jul 2023 11:19
This course introduces computational methods in Physics. 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 |
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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 concludes the course.
Information on contact teaching time is available from the course guide.
Assessment Type | Summative | Weighting | 60 | |
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Assessment Weeks | Feedback Weeks | |||
Feedback |
Written feedback via MyAberdeen |
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
Procedural | Apply | Work on developing your own mathematical programming project |
Procedural | Understand | Basic programming concepts: algorithms, loops, conditional statements, functions, etc |
Procedural | Understand | Linear algebra, random numbers and numerical integration |
Procedural | Understand | numpy and matplotlib scientific libraries for data analysis and plotting |
Assessment Type | Summative | Weighting | 40 | |
---|---|---|---|---|
Assessment Weeks | Feedback Weeks | |||
Feedback |
Written feedback via MyAberdeen |
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
Procedural | Understand | Basic programming concepts: algorithms, loops, conditional statements, functions, etc |
Procedural | Understand | Linear algebra, random numbers and numerical integration |
Procedural | Understand | numpy and matplotlib scientific libraries for data analysis and plotting |
There are no assessments for this course.
Assessment Type | Summative | Weighting | 100 | |
---|---|---|---|---|
Assessment Weeks | Feedback Weeks | |||
Feedback |
Written feedback via MyAberdeen |
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
|
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
Procedural | Understand | Basic programming concepts: algorithms, loops, conditional statements, functions, etc |
Procedural | Understand | numpy and matplotlib scientific libraries for data analysis and plotting |
Procedural | Understand | Linear algebra, random numbers and numerical integration |
Procedural | Apply | Work on developing your own mathematical programming project |
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