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Academic Handbook MA Philosophy and Artificial Intelligence (Subject to Approval)

Introduction to Programming Course Descriptor

Course code LCSCI7238 Discipline Computer Science
UK Credit N/A (non-accredited) US Credit NA
FHEQ level N/A Date approved June 2023
Core attributes N/A
Pre-requisites None
Co-requisites None

Course Overview

By the end of this course, students will be able to implement code in Python to a beginner level. Students will understand the basics of implementing code and working with data. The course covers the construction of data structures using dictionaries, sets, tuples, lists and arrays. It also covers functions and control flow using conditionals and loops as well as implementing mathematical concepts from probability and calculus using Python.

Learning Outcomes

On successful completion of the course, students will be able to:

Knowledge and Understanding

K1d Attain fundamental principles of software development such as abstraction, data representation, and logic
K2d Demonstrate evidence of problem-solving using concepts from computer science

Subject Specific Skills

S1d Construct programs using key features in Python to model problems and represent information using abstraction

Transferable and Professional Skills

T1d Identify and analyse problems to design appropriate solutions
T3d Work with peers on a project to envision a solution to a computing problem
T4d Work effectively and independently through reflective practice

Teaching and Learning

This course has a dedicated Virtual Learning Environment (VLE) page with a syllabus and range of learning resources to orientate and engage students in their studies. All scheduled teaching and learning activities for this course are delivered online via the VLE.

Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.

Indicative Reading

Note: Comprehensive and current reading lists for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative reading list provided below is used as part of the approval/modification process only.


  • Montfort, N. (2021). Exploratory programming for the arts and humanities. MIT Press.
  • Python Software Foundation (2023). The Python Tutorial. Python Software Foundation
  • Spiegelhalter, D. (2019). The art of statistics: Learning from data. Penguin UK.

Indicative Topics

Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students. The indicative topics provided below are used as a general guide and part of the approval/modification process only.

  • Introduction to Python
  • Data representation
  • Control Flow
  • Probability and Calculus

Version History

Title: LCSCI7238 Introduction to Programming

Approved by: Academic Board

Location: Academic Handbook/Programme specifications and Handbooks/ Postgraduate Programme Specifications/

Version number Date approved Date published Owner Proposed next review date Modification (As per AQF4) & category number
1.0 June 2023 June 2023 Alexandros Koliousis April 2028  
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