Module Catalogue 2023/24

CSC8621 : Computing Foundations of Data Science

  • Offered for Year: 2023/24
  • Module Leader(s): Dr Jennifer Warrender
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semester 1 Credit Value: 10
ECTS Credits: 5.0
Pre Requisites
Pre Requisite Comment


Co Requisites
Co Requisite Comment



This module aims to introduce the fundamental computing concepts and techniques underpinning contemporary data science. The module aims to provide students with a grounding in program design and implementation, programming environments. Furthermore, it explores how to apply and devise algorithms for a particular problem.

This module places an emphasis on clear design and development of programs, teaching how to break problems down to provide simpler and easier-to-use solutions. Students will apply these skills at a practical level with a particular programming language, though the skills learned here can be applied to any programming language.

Outline Of Syllabus

-       What is programming?
-       The building blocks and structure of computer programs.
-       Tackling data analysis problems.
-       Algorithms and some examples.
-       Introduction to a programming language, and relevant libraries, for data analysis.
-       Methods and data structures for data analysis.
-       Case studies in software development within a data science context.

Learning Outcomes

Intended Knowledge Outcomes

At the end of the module students will have:
- A knowledge of what is meant by programming a computer.
- An understanding of how to break down a problem into a form suitable for solving with a program.
- An appreciation of what algorithms are and how to devise them.
- A knowledge of how to design, implement, test and debug software.
- An understanding of the application of computer programming to data analysis problems.

Intended Skill Outcomes

At the end of the module, students will be expected to be able to devise a programmatic approach to problem solving, and to use a programming language and software development environments to design, implement, test, and debug programs.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion122:0024:00Lecture follow-up includes time for formative exercises
Scheduled Learning And Teaching ActivitiesLecture81:008:00Synchronous present in person (pip) tutorial sessions.
Structured Guided LearningLecture materials121:0012:00Asynchronous online materials
Guided Independent StudyAssessment preparation and completion120:0020:00Practical/lab report assessments
Scheduled Learning And Teaching ActivitiesPractical82:0016:00Synchronous present in person (pip) practical sessions.
Guided Independent StudyIndependent study120:0020:00Background Reading
Teaching Rationale And Relationship

Lectures materials are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Lecture follow-up, e.g., quizzes and exercises, is associated with each lecture in order to provide sufficient hands-on training and rapid feedback on understanding. Scheduled sessions are used both for solution of problems and work requiring extensive computation and to give insight into the ideas/methods studied.

Reading Lists

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Practical/lab report1M100Programming assignment
Formative Assessments
Description Semester When Set Comment
Prob solv exercises1MPractical/Tutorial exercises
Assessment Rationale And Relationship

Programming assignment allows the students to develop their problem-solving techniques, to practise the methods learned in the module, to assess their progress and to receive feedback.

Students will be given a formative exercise to introduce them to relevant tools, develop their understanding of programming concepts and provide them with the opportunity to gain experience through practical application.


Past Exam Papers

General Notes


Disclaimer: The information contained within the Module Catalogue relates to the 2023/24 academic year. In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described. Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2024/25 entry will be published here in early-April 2024. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.