COMP42215: Introduction to Computer Science

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• To introduce students to the key concepts of programming in python
• To examine how data structures affect the ease of implementation and efficiency of computer programs
• To give students an in-depth understanding at an advanced level of data structures appropriate to data science
• To provide an in-depth understanding and critical evaluation of specialist techniques in software engineering and their relevance to data science

• This module is intended for students whose first degree is not in computer science or related disciplines
• All examples will be given with the python programming language. It is assumed that students will already be aware of python, from pre-course reading and preparation.
• Programming in python
• Data structures and their impact on execution time
• Algorithmic complexity
• Modern software engineering techniques e.g. source-code control, automated testing.

Subject-specific Knowledge:

• By the end of this module, students should:
• Understand the core constructs of imperative programming and how they are used in python
• Have a critical appreciation of the main strengths and weaknesses of a range of programming data structures and how to use them
• Have a critical appreciation of modern software engineering techniques

Subject-specific Skills:

• By the end of this module, students should:
• Be able to write computer programs in python
• Be able to select appropriate data structures for modelling various data science scenarios
• Be able to evaluate the complexity of an algorithm
• Be able to use appropriate tools to manage source code
• Be able to use appropriate tools to test code automatically

Key Skills:

• Effective written communication
• Planning, organising and time-management
• Problem solving and analysis

• This module will be delivered by the Department of Computer Science
• Learning outcomes are met through practical workshops, supported by online resources. The workshops consist of a combination of taught input, groupwork, case studies, discussion and computing labs. Online resources provide preparatory material for the workshops, typically consisting of directed reading and video content.
• The summative assessment is an individual written report on the design, implementation, analysis and testing of a program to solve a specified data science problem
• Teaching on this module will be delivered in a blended mode with specific elements delivered online where student numbers determine online teaching as the most effective method

The formative assessment consists of classroom-based exercises involving individual and group tasks on specific computer science topics, relevant to the learning outcomes of the modules. Oral and written feedback will be given on a group and/or individual basis as appropriate.

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