The course introduces students to object-oriented programming, the programming language Python and its use for data programming and analytics.

The teaching material mostly consists of asynchronous content.

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100% Continuous Assessment

This will typically be made up of a project (25%), and three homework exercises (75%). Full details are provided in the programme handbook.

The aims of this course are:

■ to introduce students to object-oriented programming and Python as a generic programming language;

■ to train students in Python libraries relevant to data analytics such as scikit-learn, NumPy/SciPy and pandas

By the end of this course students will be able to:

■ design and implement functions and classes in Python;

■ make efficient use of the data structures built into Python, such as lists;

■ describe and exploit features of object-oriented design such as polymorphism and inheritance

■ implement data management tasks in Python;

■ implement data-analytic tasks in Python using external libraries such as scikit-learn, NumPy/SciPy and pandas

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.