Data Science MSc

Program Overview

Teesside University's MSc Data Science program equips students with the skills and knowledge to excel in the field of data science. Led by experienced faculty, the program offers a range of modules covering core concepts and advanced topics, including machine learning, data visualization, and research methods. Graduates are prepared for careers in various industries, with opportunities for internships and research projects to enhance their practical experience.

Program Outline

Data Science MSc Course at Teesside University:

Degree Overview:

This MSc Data Science course, offered by Teesside University, equips students with the specialist skills and knowledge to make an immediate and meaningful contribution to various industry environments. The program features:

• Expertise: Led by experienced staff from the University's renowned machine intelligence research group, ensuring access to the latest thinking in the field of data science.
• Research Opportunities: Students have the chance to contribute to live research projects and potentially progress to postgraduate research opportunities.
• Industry Relevance: The program draws on real-world case studies from the University's successful collaborations with industry partners, ensuring students gain practical and applicable knowledge.

Outline:

• Course structure: The program offers three routes to completion:
• Full-time with advanced practice (2 years, starting in September or January)
• Full-time (1 year, starting in September or 16 months, starting in January)
• Part-time (2 years)
• Modules:
• Core modules:
• Big Data and Business Intelligence: Develop the ability to design and implement database, big data, and analytics applications to meet business needs.
• Computing Masters Project: Conduct in-depth research and produce a major deliverable, such as a software package or design project.
• Data Visualisation: Explore and utilize various data visualization techniques, including traditional and novel charts, to effectively communicate information.
• Interactive Visualisation: Master the use of dynamic, interactive visualizations to enhance data exploration and discovery.
• Machine Learning: delve into the principles and methods of machine learning, focusing on building models for prediction and analysis.
• Research Methods: Equip yourself with the essential research skills and knowledge to undertake your masters project.
• Statistical Methods for Data Analytics: Gain a deep understanding of quantitative and qualitative data analysis techniques, including correlation testing, regression, and data normalization.
• Advanced practice (2 year full-time MSc only):
• Internship: Choose between a vocational internship to gain practical industry experience or a research internship to develop your research skills within the University.
• Course Schedule: Information on the specific schedule for each module is not provided in the context.
• Individual Modules:
• Detailed descriptions of individual modules are available at the program's website.

Assessment:

• Assessment strategy: Designed to assess subject-specific knowledge, cognitive and intellectual skills, and transferable skills applicable to the workplace.
• Formative and summative assessments: Provide opportunities for development and feedback throughout the program.
• Assessment types: Assignments, tests, case studies, presentations, research proposals, literature reviews, and a dissertation.
• Assessment criteria: May include presentation skills, report writing, and critical analysis of research findings.

Teaching:

• Learning methods: Concepts and methods are taught through keynote lectures, tutorials, and case studies.
• Guest speakers: Industry experts provide insights and perspectives through guest lectures.
• Critical reflection: Encouraged as a key element in developing students' problem-solving and creative thinking skills.
• Faculty: The program is delivered by experienced and passionate staff from the University's machine intelligence research group.

Careers:

• Career preparation: The program equips graduates with the skills and knowledge necessary to thrive in the growing field of data science.
• Networking opportunities: Events such as ExpoSeries facilitate interaction with industry partners and potential employers.
• Career opportunities: Graduates can find employment in various sectors, such as the defense industry, finance, telecommunications, and healthcare.

Other:

• Entry requirements: A first degree in a related discipline (2.2 minimum) or relevant experience or equivalent qualifications.
• Fees:
• UK applicants: £7,365 per year (full-time), £4,770 per year with advanced practice.
• International applicants: £17,000 per year (full-time), £10,000 per year with advanced practice.
• Information for international applicants:
• Specific qualifications requirements based on country of origin are available on the program website.
• Visit the University's international pages for further information and support.
For more details on the Data Science MSc course at Teesside University, please refer to the program's website or contact the University directly.

Tuition Fees and Payment Information:

Full-time

2024/25 entry Fee for UK applicants £7,365 a year £4,770 a year with advanced practice Fee for international applicants £17,000 a year £10,000 a year with advanced practice

Part-time

2024/25 entry Fee for UK applicants £820 for each 20 credits