F78AP - Algorithmic and Scientific Programming
Course leader(s):
Syllabus
1.1 1. Numerical and graphical summaries of data, 1.2 2. Workbooks and worksheets; the ribbon, 1.3 3. Creating formulas and functions
2. Algorithmic Programming (2.1 1. Introduction to computational algorithms, 2.2 2. Conditional statements and loops, 2.3 3. Functions and recursion, 2.4 4. Vectors, arrays and matrices, 2.5 5. Graphics, 2.6 , 2.7 Topics to be covered using at least two programming languages eg, R and Python)
Learning outcomes
By the end of the course, students should be able to do the following:
- systematically analyse the structure and operation of unfamiliar algorithms and computer programmes.
- design algorithms to solve unfamiliar mathematical and statistical problems using appropriate control structures, loops, conditional statements and data structures.
- write computer programmes implementing algorithms to solve mathematical and statistical problems using appropriate software.
- use Excel to produce graphical and numerical summaries of data and solve numerical problems.
- create simple formulae in Excel to solve statistical, mathematical and computational problems.
- apply appropriate algorithms and computer programmes to solve problems relevant to modern data science and related industries.
- apply their understanding of computer programming to independent study of unfamiliar programming languages.
Further details
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SCQF Level: 8
Credits: 15
