DSC8003 : Foundations of Data Science
- Offered for Year: 2025/26
- Module Leader(s): Dr Aamir Khan
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Aims
This module provides an introduction to the fundamental mathematical and statistical concepts and techniques that form the basis of data science.
Outline Of Syllabus
Introductory calculus (e.g. limits, sequences and series, differentiation, integration); introductory algebra (e.g. algebraic manipulation, functions and relations, set theory, combinatorics, linear algebra); introductory probability (including axioms, counting, conditional probability, random variables); standard distributions and modelling (including joint, marginal and conditional distributions, transformations and functions of random variables); estimation (primarily likelihood-based methods); regression (including linear and generalised linear models); classification.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 1 | 2:30 | 2:30 | Digital exam (NUMBAS) |
| Scheduled Learning And Teaching Activities | Lecture | 2 | 1:00 | 2:00 | Revision lectures |
| Guided Independent Study | Assessment preparation and completion | 40 | 2:00 | 80:00 | Background reading on lecture content |
| Scheduled Learning And Teaching Activities | Lecture | 44 | 1:00 | 44:00 | Lectures |
| Guided Independent Study | Assessment preparation and completion | 1 | 0:40 | 0:40 | Problem solving exercise (40 min class test) |
| Guided Independent Study | Assessment preparation and completion | 1 | 20:00 | 20:00 | Revision for unseen digital exam |
| Scheduled Learning And Teaching Activities | Small group teaching | 10 | 1:00 | 10:00 | Tutorials/Problem Classes |
| Guided Independent Study | Independent study | 1 | 40:50 | 40:50 | Independent Study |
| Total | 200:00 |
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. Problem classes are used to help develop the students’ abilities at applying the theory to solving problems.
The teaching methods are appropriate to allow students to develop a wide range of skills. From understanding basic concepts and facts to higher-order thinking.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Digital Examination | 150 | 1 | A | 80 | Digital exam (NUMBAS) |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Prob solv exercises | 1 | M | 20 | 40 minute class test (NUMBAS), conducted during one of the timetabled lecture/tutorial slots |
Assessment Rationale And Relationship
A substantial formal unseen examination is appropriate for the assessment of the material in this module. The format of the examination will enable students to reliably demonstrate their own knowledge, understanding and application of learning outcomes.
Examination problems may require a synthesis of concepts and strategies from different sections, while they may have more than one way for solution. The examination time allows the students to test different strategies, work out examples and gather evidence for deciding on an effective strategy, while carefully articulating their ideas and explicitly citing the theory they are using.
The coursework assignments 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 summative assessment has a secondary formative purpose as well as its primary summative purpose.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- DSC8003's Timetable