KL7010 - Principles of Data Science

APPLY NOW BOOK A VIRTUAL OPEN DAY Add to My Courses Register your interest / Course PDF

What will I learn on this module?

In this module, you will learn data science lifecycle and foundations, principles, and fundamental statistical methods, techniques and applications in data science. You will explore key areas of data science including question and hypotheses formulation, data collection and cleaning, visualization, statistical inference, predictive modelling, and decision-making. You will learn fundamental aspects of probability and statistics to equip you to lead standard data analysis projects in industry and research. The module will covers broad topics such as:

• Foundations of Data Science
• Principles and techniques of Data Science
• Review and evaluation of Data Science methods, techniques and tools

How will I learn on this module?

The module includes a combination of methods to support learning, including lectures and computer based seminars/workshops allowing you to put the theory from lectures into practice. Topics will normally be introduced in lectures and explored through real world examples and practical exercises (helping you develop the required knowledge and understanding) and guided learning activities. You will be encouraged to develop independent learning skills to explore further in the subject area and take benefit from Northumbria University’s Enterprise Data Analytic Clinic organised by the Institute of Coding (IoC).

How will I be supported academically on this module?

You will be given advice and feedback on your formative assessment (e.g., lab exercises) during the timetabled classes. In addition, the module’s site on the Blackboard Learning Portal will be used to provide extensive supporting material. You will be given detailed feedback on your summative assignment clearly identifying both the weaknesses and strong points of the work.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

What will I be expected to achieve?

Knowledge & Understanding:
1. Demonstrate critical understanding of foundations and principles of data science
2. Demonstrate deep knowledge of fundamental statistical methods, techniques and applications in data science

Intellectual / Professional skills & abilities:
3. Critically assess, select, and apply data collection and cleaning, visualization, statistical inference, predictive modelling, and decision making for statistical analysis in the context of applied data analysis problems
4. Critically evaluate the choice of data science techniques and tools for particular scenarios

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Build a critical awareness of professional, legal, cultural and ethical issues surrounding analysis, exploration, protection and dissemination of data in the context of your role as a data scientist

How will I be assessed?

Formative assessment: Exercises provided and carried out within practical classes and workshops will build up to form a basis of the summative assessment. Feedback will be given during these practical classes and workshops and/or through discussions on the Blackboard Learning Portal’s discussion board.


Summative assessments: A written assignment (4000 words)– to select, apply and evaluate a choice of data science methods, techniques, and tools on a sizeable dataset (100%) and will test MLOs 1, 2, 3, 4 and 5.

Feedback: You will be given detailed feedback on the assignment clearly identifying both the weaknesses and strong points of the work.

Pre-requisite(s)

An undergraduate degree with major in computing and information sciences or mathematical and statistical disciplines with applied computing components

Co-requisite(s)

None

Module abstract

The aim of this module is to provide you with the data science lifecycle and foundations and principles of data science, and fundamental statistical methods, techniques and applications in data science. It explores key areas of data science including question formulation, data collection and cleaning, visualization, statistical inference, predictive modelling, and decision-making. It will help you learn about fundamental aspects of probability and statistics to equip you to lead standard data analysis projects in industry and research. The module will teach you how to use probability to deal with uncertainty, ways of visualizing and preparing data for statistical analysis in the context of applied data analysis problems, and hypothesis testing, predictive analysis from the point of view of regression. The module will covers topics such as foundations of Data Science including visualisation, hypothesis testing, prediction and regression; principles and techniques of Data Science including the Data Science Lifecycle, Data Design, Exploratory Data Analysis, Data Cleaning, Probability and Generalization, Linear Regression, Classification and Statistical Inference.

This module includes a combination of methods to support learning, including lectures and lab based seminars/workshops allowing you to put the theory from lectures into practice. Topics will normally be introduced in lectures and explored further through real world examples and practical exercises (helping you develop the knowledge and understanding needed) and guided independent learning activities. You will be encouraged to develop independent learning skills to explore further in the field of data science and take benefit from Northumbria University’s Enterprise Data Analytic Clinic through the Institute of Coding (IoC) within the CIS department.

Course info

Credits 20

Level of Study Postgraduate

Mode of Study 2 years full-time with Advanced Practice
2 other options available

Location City Campus, Northumbria University

City Newcastle

Start September 2020

Fee Information

Module Information

Current, Relevant and Inspiring

We continuously review and improve course content in consultation with our students and employers. To make sure we can inform you of any changes to your course register for updates on the course page.

Your Learning Experience find out about our distinctive approach at 
www.northumbria.ac.uk/exp

Admissions Terms and Conditions - northumbria.ac.uk/terms
Fees and Funding - northumbria.ac.uk/fees
Admissions Policy - northumbria.ac.uk/adpolicy
Admissions Complaints Policy - northumbria.ac.uk/complaints