As scientific methods and instruments advance, computers become ever more important in data analysis and acquisition. This module introduces to the concept of programming languages and their uses, and presents a practically minded course on using simple programming to solve problems relevant to chemistry, and to automate the analysis and presentation of data.
Private Study: 114
Contact Hours: 36
Total: 150
Not available as a elective module.
• Coding Assignment 1 (3 hours) – 10%
• Coding Assignment 2 (3 hours) – 10%
• Coding Assignment 3 (6 hours) – 20%
• Coding Assignment 4 (6 hours) – 20%
• Coding Assignment 5 (6 hours) – 20%
• Coding Assignment 6 (6 hours) – 20%
The University is committed to ensuring that core reading materials are in accessible electronic format in line with the Kent Inclusive Practices. The most up to date reading list for each module can be found on the university's reading list pages.
1. Demonstrate a systematic understanding of how computers work according to human instruction;
2. Demonstrate knowledge and understanding of computing languages and principles, and their use for diverse applications;
3. Demonstrate an ability to solve problems in mathematics and chemistry using appropriate mathematical tools. This includes the ability to use computational methods for the practical application of theory and to use information technology and data-processing skills to search for, assess and interpret chemical information and data.
4. Demonstrate an ability to use mathematical techniques and analysis to model physical behaviour using computer programming.
5. Demonstrate competent use of appropriate C&IT packages/systems for the analysis of data and the retrieval of appropriate information.
6. Demonstrate an ability to present and interpret information graphically using a computer.
7. Demonstrate an ability to make use of appropriate texts, research-based materials or other learning resources as part of managing their own learning, and develop simple algorithms.
8. Demonstrate an ability to recognise and analyse problems and plan strategies for their solution by the evaluation, interpretation and synthesis of scientific information and data. Ability to adapt and apply methodology above to solve advanced and unfamiliar problems found in computer programming.
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