Postgraduate Course: Python Programming (MATH11199)

Course Outline
School	School of Mathematics	College	College of Science and Engineering
Credit level (Normal year taken)	SCQF Level 11 (Postgraduate)	Availability	Not available to visiting students
SCQF Credits	10	ECTS Credits	5
Summary	The practical use of computing to support mathematics is of key interest to those who wish to apply mathematics to real-world problems. This course will seek to introduce modern programming concepts and development methods to students with little or no background in computing using the computing language Python. * This course is available to Mathematics MSc students only. *
Course description	This course introduces modern programming concepts and practice for students with little or no background in computing using the computer language Python. The course will start with a presentation of basic programming concepts, including data types and structures as they exist in Python. Loops and conditional statements will then be introduced, as well as custom functions, along with a wider discussion of structured programming and ways to reuse code. Students will then consider practical applications of programming. They will learn to work with data input and output in different formats, use suitable libraries for scientific computing and data analysis, and create plots and visualisations to display results. Throughout the course, students will engage with professional programming practices and tools (test-driven development, version control, code reviewing, debugging), and will have the opportunity to collaborate with peers to develop their skills.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites		Co-requisites
Prohibited Combinations		Other requirements	This course is only available to Mathematics MSc and Finance, Technology & Policy MSc students.

Course Delivery Information

Academic year 2022/23, Not available to visiting students (SS1)		Quota: None
Course Start	Semester 1
Timetable	Timetable
Learning and Teaching activities (Further Info)	Total Hours: 100 ( Lecture Hours 10, Supervised Practical/Workshop/Studio Hours 20, Summative Assessment Hours 1, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 67 )
Assessment (Further Info)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment)	Coursework :100% Coursework consists of weekly formative assessment (total 20%) and two programming projects (40% each).
Feedback	Not entered
No Exam Information

Learning Outcomes
On completion of this course, the student will be able to: Design and implement Python programs to solve a range of mathematical problems. Select and use appropriate libraries and data structures to perform computational analyses in Python; consult the relevant documentation. Review a Python program to explain the underlying logic, identify and fix bugs, and suggest improvements to structure and style. Collaborate with peers on programming tasks, using suitable tools. Use Python to carry out investigations on data and extract key insights; display and discuss results in a well-presented report.