Study information

Programming with Python - 2025 entry

MODULE TITLEProgramming with Python CREDIT VALUE15
MODULE CODECOM2016 MODULE CONVENERDr Phil Lewis (Coordinator)
DURATION: TERM 1 2 3
DURATION: WEEKS 11 (October starters) 11 (January starters)
Number of Students Taking Module (anticipated)
DESCRIPTION - summary of the module content
This module will introduce students to the fundamentals of constructing software using the Python programming language. You will learn how to decompose problems into components that can be implemented to provide a software solution, as well as how to control program flow and represent data within software. Having learned the fundamentals of Python coding you will be introduced to exception handling, Python classes, and be introduced to principles of software development and testing.
 
This module cannot be taken with BEM1025 Programming for Business Analytics.
AIMS - intentions of the module

This module will ensure that students are able to create software solutions to problems arising in a variety of fields and industries. They will learn concepts that enable them to implement software using Python efficiently, as well as assuring the software is correct using code testing.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

1. Implement software to solve a given problem that utilises the control structures and data structures available in the Python language.

2. Understand how to build applications that make use of Python libraries as required by the problem.

Discipline Specific Skills and Knowledge

3. Systematically break down a problem into its components and design a solution using appropriate programming approaches. 

4. Use industry-standard approaches for software development and testing, including how to use AI coding tools.

Personal and Key Transferable / Employment Skills and Knowledge

5. Formulate a software design to a problem from a given field or industry beyond computer science or data science.

 

SYLLABUS PLAN - summary of the structure and academic content of the module

The module will cover the following topics:

• Problem decomposition and program design.

• Foundational Python concepts (e.g. types and program structure).

• Control structures (conditionals, loops).

• Python data structures.

• Exception handling.

• Object orientation.

• Event-driven programming.

• Design patterns.

• Software testing and using AI coding tools.

• Deployment.

LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 44 Guided Independent Study 106 Placement / Study Abroad 0
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS

Category

Hours of study time

Description

Scheduled learning and teaching activities

22

Lectures

Scheduled learning and teaching activities

22

Workshops

Guided independent study

50

Programming exercises

Guided independent study

56

Lecture and assessment preparation

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade

Form of Assessment

Size of Assessment (e.g. duration/length)

ILOs Assessed

Feedback Method

Workshop exercises

1 hour per week

ALL

Model answers and verbal feedback

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 70 Written Exams 30 Practical Exams 0
DETAILS OF SUMMATIVE ASSESSMENT

Form of Assessment

% of Credit

Size of Assessment (e.g. duration/length)

ILOs Assessed

Feedback Method

Exam

30

1 hour

1, 2

Written

Coursework

70

30 hours

ALL

Written

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-assessment
Exam Exam (1 hour, 30%) 1,2 Referral/deferral period
Coursework Coursework (30 hours, 70%) ALL Referral/deferral period

 

RE-ASSESSMENT NOTES

Deferral – if you have been deferred for any assessment you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 40%) you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of referral will be capped at 40%

 
RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Basic reading:

  • Matthes, Eric  Python crash course a hands-on, project-based introduction to programming. ISBN : 9781718502710
  • Allen B. Downey, “Think Python: How to think like a Computer Scientist”, O’Reilly Media, 2012. ISBN: 978-1449330729.

Other Resources:

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE 15 ECTS VALUE 7.5
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) 5 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Wednesday 13th March 2024 LAST REVISION DATE Thursday 25th September 2025
KEY WORDS SEARCH Computer; programming; data; algorithms; problem solving; Python

Please note that all modules are subject to change, please get in touch if you have any questions about this module.