Core Module Information
Module title: Fundamentals of Python for Data Science

SCQF level: 07:
SCQF credit value: 10.00
ECTS credit value: 5

Module code: SET07202
Module leader: Sally Smith
School School of Computing, Engineering and the Built Environment
Subject area group: Computer Science
Prerequisites

N/A

Description of module content:

The module provides a fundamental introduction to python and makes no assumptions about your prior exposure to it. The latter parts of the module will focus on applying these concepts to data processing, such that you will develop insight into automating common statistical analyses on imported datasets.

The syllabus includes topics such as:
• An introduction to building scripts using a popular scripting language widely used in Data Science
• Core programming and language concepts, such as data types, control structures, functions, importing libraries, and re-usable design
• Techniques for creating robust scripts, including exception handling, testing and debugging

The chosen scripting language is widely used by Data Scientists in both academia and industry and has a thriving community which provides supporting software packages of relevance to the programme of study.

Learning Outcomes for module:

LO1: Design, implement and test software scripts which solve problems relating to statistics and data science

LO2: Employ good practice programming and scripting techniques to develop well-written modular code which is reusable, well documented and uses comprehensive error handling techniques.

Full Details of Teaching and Assessment
2023/4, Trimester 3, ONLINE,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: ONLINE
Location of delivery: MERCHISTON
Partner:
Member of staff responsible for delivering module: Sally Smith
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Online Lecture 12
Online Practical classes and workshops 12
Independent Learning Guided independent study 64
Online Demonstration 12
Total Study Hours100
Expected Total Study Hours for Module100


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Project - Practical 100 LO1, LO2 13 HOURS= 12.00
Component 1 subtotal: 100
Component 2 subtotal: 0
Module subtotal: 100

Indicative References and Reading List - URL:
Contact your module leader