ULMS Electronic Module Catalogue
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title Introduction to Programming (Python)
Code ACFI827
Coordinator Dr S Sachan
Finance and Accounting
Swati.Sachan@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2024-25 Level 7 FHEQ First Semester 15

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):
 

Modules for which this module is a pre-requisite:
 

Programme(s) (including Year of Study) to which this module is available on a required basis:
 

Programme(s) (including Year of Study) to which this module is available on an optional basis:
 

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 10

     20

     30
Timetable (if known)              
Private Study 120
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
             
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Group report Reassessment opportunity: Yes Penalty for late submission: Standard UoL penalty applies Anonymous assessment: No  0    40       
Individual report Reassessment opportunity: Yes Penalty for late submission: Standard UoL penalty applies Anonymous assessment: Yes  0    60       

Aims

This module aims to provide students with an understanding of programming using ‘Python for Finance’. No prior knowledge of either coding or Python is assumed. The aim of the module is not to create coding experts but rather an appreciation of coding to at least a working level which is fundamental to a holistic understanding of applied commercial FinTech in practice and associated research. Nonetheless, students who have prior knowledge of coding (in Python or other languages) will have the space to expand and improve upon their knowledge and skills.

Learning Outcomes

(LO1) Students will be able to carry out analysis, design and implementation of algorithms using Python.

(LO2) Students will be able to demonstrate knowledge and understanding of writing structured computer programs.

(LO3) Students will be able to select appropriate Python Functions to solve business/ coding problems.

(LO4) Students will be able to explore example libraries within Python and establish an understanding of how to access advanced features to solve evolving needs in coding.

(LO5) Students will be able to implement their Python skills to broader research tasks and evaluate the potential application of Python to real-world opportunities in FinTech.

(S1) Flexibility and adaptability.
Students will develop their adaptability skills by using the Python language creatively for a range of business and coding issues.

(S2) Problem-solving.
Students will engage in the creative application of logic in coding.

(S3) Numeracy.
Students will develop numeracy skills through general coding application and the use of Python as a calculator.

(S4) Organisation skills.
Students will need to be organised throughout the duration of the module in order to prepare the required reading for lectures and seminars and in preparation for the two assignments.

(S5) Communication skills.
Students will develop their communication skills through their assessed work.

(S6) IT skills.
Students will establish proficiency or further advancement in Python programming.

(S7) Organisation skills.
Students will develop their organisation skills in approaching a Python programming problem of logic.

(S8) Lifelong learning.
Students will appreciate the power and versatility of coding using Python and other programming languages to help solve future research and commercial questions.

(S9) Collaborative coding skills.
Students will develop collaborative coding skills essential for working in data science or technical project teams in the industry.

Teaching and Learning Strategies

1 hour lecture x 10 weeks
2 hour labs x 10 weeks
120 hours Self-directed learning

Outside of the classroom, students will be expected to engage in wider reading in the form of journals, books and recordings as directed by the module leader. The framework/ scaffolding for such learning will be provided on the VLE by the module leader.

HiPy and other peer-to-peer learning platforms may be adopted where relevant in the pedagogic strategy of this module delivery.

Syllabus
 

Getting started with Python:
- Python integrated development environment (IDLE) such as Spyder, PyCharm, and Jupyter Lab
- Version control by GitHub

Python Basics I (e.g. Math, Strings and standard math operations);

Python Basics II (e.g. Order of operations, spacing, number types (Integers and floats), complex numbers & floats);

Strings: concatenation, methods and input;

Building Functions I (e.g. IF statements, While Loops, For Loops and Building Functions);

Building Functions II and Python structures;

Introduction to libraries;

Library I: NumPy;

Library II: Pandas;

Library III: Matplotlib;

Pyplot and Dates and Times;

Executing Python Programs.

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.