Cardiff School of Technologies>Courses>Data Science - MSc/PgD/PgC

Data Science Masters Degree - MSc/PgD/PgC

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This Master's degree in Data Science is an industry-relevant and popular postgraduate programme of study. Data Science and "Big Data" are more important than ever. Graduates trained to garner insights from large data sets, extract patterns and provide actionable information to solve real-world problems are sought after in both the private and public sector.

This course will equip you with in-demand theoretical knowledge and practical skills to develop data science systems, use software to analyse and synthesise data, and manage all aspects of data science.


This degree will undergo a periodic review in 2023/4 to ensure the course content is and remains current. Should any changes to course content be made as a result of the review, all applicants will be informed once changes are confirmed.


Course Content

Compulsory modules:

  • Technology Project Management (20 credits)
  • This module aims to foster in students a critical appreciation of project management principles and practices in preparation for when they will manage – or be managed via – technology projects.

  • Business Process & Data Analysis (20 credits)
  • This module is designed to enable the student to develop a critical appreciation of a range of business process analysis approaches and to explore key contemporary issues regarding their application in organisations.

  • Geospatial Analysis (20 credits)
  • This module aims to provide students with the opportunity to gain experience and develop skills in handling spatial data, and to both identify and understand any patterns revealed within that data through the application of various techniques in spatial analysis.

  • Programming for Data Analysis (20 credits)
  • The aim of this module is to help students acquire skills for job roles of Data Scientist, Data Modellers and Data Analyst. Students taking this module will have the opportunity to understand and implement various statistical and computational techniques for analysing datasets using various industry standard software and programming languages.

  • Research Methods for Technology Dissertations (20 credits)
  • The aim of this module is to equip the student with the skills, knowledge and techniques necessary to produce a dissertation with a research or technical focus.

  • Social Media Analytics for Business (20 credits)
  • This module provides students with the opportunity to gain experience and develop skills in handling social media data that is generated from user activity.

  • Technology Dissertation (40 credits)
  • The aim of the technology project is for the student to apply knowledge, skills and techniques developed during directed and independent study to solve a real world technology related project. The technology project may take the form of an in-depth research project or the development of a computer system.

  • Information Security (20 credits)
  • This module aims to provide an insight into the implementation of data security in computer systems and to encourage students to appreciate the practical and theoretical management principles associated with information security.

To obtain an MSc degree, you must follow and successfully complete a total of 180 credits. PgC (60 credits) and PgD (120 credits) may be awarded as standalone or exit awards.

Learning & Teaching

A range of teaching methods are used in Cardiff School of Technologies, including studios, practical workshops, tutorials, seminars, and real-world case studies, all supported by online learning via Moodle. With a student-centred approach, the school operates an open-door policy to staff and all students will be assigned a personal tutor. 

Studios 

Studios are a major part of the teaching strategy for the programme. Studios are an effective way of delivering core material and establishing a framework for a module against which other material can be set. Unlike a typical lecture theatre setting, these sessions enable more interactions among the lecturers and group of students. 

Practical Workshops

In these sessions, students can practice and refine their skills in a supportive environment where they can receive feedback from a member of academic staff. Practical workshops represent a valuable transition between theory and the workplace. These sessions also involve tutorials where a students or group of students can meet with their tutor and are used in two ways within the programme:
(a) expanding upon material covered in lectures through an enquiry-driven problem-solving approach
(b) remedial work to overcome any deficiencies in a student's background knowledge.

Seminars

Seminars involve a student or students presenting previously prepared work to peers and a lecturer. This strategy is used to extend specific theoretical or practical concepts as well as introducing problem solving exercises. Seminars are used in most modules and provide students with valuable experience in presentational skills as well as providing staff with a method of assessing student-centred learning. These sessions can be conducted either in standalone manner or can be combined with studios or workshops as well, depending upon the learning objectives of a specific module. 

Case Studies 

Case studies are a teaching and learning strategy, employed in a range of modules; they also are a useful assessment tool. Students are presented with or asked to develop real or simulated complex problems which they are required to analyse in detail and then synthesise/present their own solution in writing or orally. 

Online learning platforms 

All modules will be supported by Moodle and MS Teams providing students with a wide range of learning material and study guidance.

Assessment

Assessments take the form of individual or group coursework, research based assignments, practical assessments, presentations, reports, class tests and a dissertation.

Employability & Careers

The specialist knowledge you will acquire through the course will place you in a strong position to pursue a wide range of careers involving the analysis of data, including data analyst, data scientist, IT consultant and managerial roles in industry. The programme also gives you a range of computing skills that could be widely applied to any role within the fields of business and computing.

Entry Requirements & How to Apply

Applicants should meet one of the following:

  • Possess, or expect to obtain, an undergraduate degree or equivalent, in a relevant area with a minimum of a 2:2 classification;
  • Hold a suitable professional qualification from an appropriate professional body.

International Students:
Students whose first language is NOT English will need to provide evidence of fluency to at least an IELTS 6.0 standard, with no element under 5.5 or equivalent.​​​​

Selection Procedure:
Application form and if necessary an interview.

How to Apply:

Applications for this course should be made direct to the university via our self-service facility. For further information please visit our How to Apply pages at www.cardiffmet.ac.uk/howtoapply.

Additional Information

International Applicants:

Before making an application, international students (those outside of the EU), should contact the International Office at Cardiff Met to discuss the necessary procedures in relation to studying with us. For further information visit www.cardiffmet.ac.uk/international.

Tuition Fees and Financial Support:

For up to date information on tuition fees and the financial support that may be available. Please refer to www.cardiffmet.ac.uk/fees.

Part-time fees:
Charges are per Single Module unless specified:
Undergraduate = 10 Credits; Postgraduate = 20 Credits

Generally we find most students will complete 60 credits per year for both Undergraduate and Postgraduate study; to obtain a true costing please clarify this by contacting the Programme Director directly. 

Contact Us

For general enquiries please contact the Admissions Team on 029 2041 6044 or email directapplications@cardiffmet.ac.uk

For course specific enquiries, please contact the Programme Director, Dr Imtiaz Hussain Khan​​​: IKhan2@cardiffmet.ac.uk

We endeavour to deliver courses as described and will not normally make changes to courses, such as course title, content, delivery, and teaching provision. However, it may be necessary for the university to make changes in the course provision before or after enrolment. It reserves the right to make variations to content or delivery methods, including discontinuation or merging courses if such action is considered necessary. Please read our Terms and Conditions for the full information.

Key Course Information

Place of Study: 
Llandaff Campus

School:
Cardiff School of Technologies

Course Length:
12-18 months full-time depending on start date, or three years part-time.

September and January intakes available.

Postgraduate Scholarships:
The university also offers a postgraduate scholarship scheme to help students whilst at university.
See if you are eligible.

Course Disclaimer
We endeavour to deliver courses as described and will not normally make changes to courses, such as course title, content, delivery, and teaching provision. However, it may be necessary for the university to make changes in the course provision before or after enrolment. It reserves the right to make variations to content or delivery methods, including discontinuation or merging courses if such action is considered necessary.

Please read our Terms and Conditions for the full information.

MEET THE TEAM

"I am an Artificial Intelligence (AI) professional with a recent focus on data science and 20+ years teaching and research experience. Data science is emerging as a microcosm of AI demanding strong background and motivation in mathematical modelling, programming and problem solving, and analytical thinking. It requires hands on experience with real-world datasets and tools such as Python, Scikit-learn, and Spark. I keep myself current and my pedagogical practice has evolved as research-led, student-centred, problem-based active learning. I believe in a strong student-teacher bond and continuously seek students and peer feedback to enhance my teaching practice."


Dr Imtiaz Hussain Khan
Senior Lecturer and Programmer Director of MSc Data Science at Cardiff School of Technologies

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