STP80080 Foundations of Data Science 1

Module CodeSTP80080
Module Name Foundations of Data Science 1
ECTS Weighting [1]5 ECTS
Semester taughtSemester 2
Module Coordinator/s Prof. Simon Wilson

Module Learning Outcomes

On successful completion of this module, students will be able to:

L01. Implement some common statistical and machine learning methods in Python.

LO2. Identify the different skills, in computer science, statistics and elsewhere, that make up the field of data science and how they work together.

LO3. Build a simple database model with data and implement simple queries using mySQL or similar language.

Module Content

Specific topics addressed in this module include: 

  • Machine learning and how it differs from statistics; non-statistical ML methods (such as case-based reasoning), regression with neural networks; classification (support vector machines, kNN);
  • Evaluating ML methods: cross validation, ROC;  Installing and running Python. Its user interface and basic operations. 
  • Introduction to databases and how data is managed, including an introduction to SQL.
  • Industry case study.

Teaching and learning Methods

This module is online with 4 weekly sessions. All content is available through Blackboard. Live online tutorials with the module lecturer or teaching demonstrator will be given.

Assessment Details

Assessment ComponentBrief Description Learning Outcomes Addressed% of totalWeek setWeek Due
Open book take home examinationOnline exam publication and submissionLO1-LO3100%N/AN/A

Reassessment Details

 100% supplemental open book take home examination

Contact Hours and Indicative Student Workload

Contact Hours (scheduled hours per student over full module), broken down by: 33 hours
Lecture33
Independent study (outside scheduled contact hours), broken down by:82 hours
Preparation for classes and review of material (including preparation for examination, if applicable42
completion of assessments (including examination, if applicable)40
Total Hours115 hours

Module Pre-requisites

None

Module Co-requisites

None

Module Website

Blackboard