Module Catalogue 2019/20

CSC8621 : Computing Foundations of Data Science

  • Offered for Year: 2019/20
  • Module Leader(s): Dr Jennifer Warrender
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 10
ECTS Credits: 5.0
Pre Requisites
Pre Requisite Comment

N/A

Co Requisites
Co Requisite Comment

N/A

Aims

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 learnt 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 compute.
- 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 completion102:0020:00Practical/Lab report exercises
Guided Independent StudyAssessment preparation and completion221:0022:00Lecture follow-up
Scheduled Learning And Teaching ActivitiesLecture221:0022:00N/A
Scheduled Learning And Teaching ActivitiesPractical221:0022:00N/A
Guided Independent StudyIndependent study141:0014:00Background reading
Total100:00
Teaching Rationale And Relationship

Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Practicals are used both for solution of problems and work requiring extensive computation and to give insight into the ideas/methods studied. A practical is associated with each lecture in order to provide sufficient hands-on training and rapid feedback on understanding.

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 report1M45Up to 3 programming assignments (1000 words as specified for each report
Report1M55Software development project and report. (Word count: up to 1500 words)
Assessment Rationale And Relationship

Programming assignments (approximately 3 pieces of work of approximately equal weight) followed by a larger piece of project work allow the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; the smaller pieces of work are thus formative as well as summative assessment.

The semi-structured interview facilitates a reflective discussion about how individual students have met the learning objectives of the module and how the principles of fundamental statistics are embedded in the functionality of their project work.

Timetable

Past Exam Papers

General Notes

N/A

Disclaimer: The information contained within the Module Catalogue relates to the 2019/20 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 2020/21 entry will be published here in early-April 2019. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.