MSc Data Science and Big Data Analytics (with Advanced Practice)
Course details
Year of entry
2025
Duration
20 weeks
Institution Code
G53
Location
Wrexham
Course Highlights
Engage
in real-world case studies
Learn
from research-active professionals
Benefit
from strong industry connections
Why choose this course?
This course aims to provide you with an opportunity to apply your knowledge and skills in a real-world environment. The course will build upon the standard MSc programme to provide you with the opportunity to enhance personal and professional development in preparation for entry into the job market.
In addition to practical and professional skills gained during their Advanced Practice placement, students will also be able to:
- Engage in critical self-reflection.
- Build self-awareness, flexibility, and resilience.
- Gain an edge in the job market through practical work experience.
You will:
- Participate in discussions, share insights, and collaborate on research projects
- Engage in hands-on, real-world case studies and industry-relevant projects, allowing you to apply your knowledge to real-world scenarios
- Develop a mindset focused on research and innovation
- Learn how to use various models, methods, tools and techniques to convert data into information
- Be taught by leading research-active professionals, on hand throughout the course to support your learning with their knowledge and expertise
- Work in a collaborative learning environment
- Benefit from connections with industry partners through guest lectures, workshops, and industry projects, providing you with networking opportunities and insights into current industry practices
Key course features
- This course will equip you with necessary technical skills to navigate and manipulate big data sets
- We have developed this course to ensure that you are equipped with cutting-edge knowledge, recognising the current and predicted future of the field
- This course will allow you to develop strong communication and problem-solving skills, allowing you to communicate your findings to a variety of audiences
- During this course, you will gain critical thinking skills, enabling you to analyse complex data problems
- This course will instil understanding of ethical considerations and responsible data handling practices, ensuring you are equipped to address ethical challenges and privacy concerns
- This course promotes a mindset of continuous learning and professional development, enabling you to stay updated with evolving trends and technologies in data science and big data analytics
What you will study
The MSc Data Science and Big Data Analytics program aims to cultivate graduates who possess expertise in the field of data science. Encompassing a broad spectrum of subjects, the program delves into areas such as machine learning techniques, implementation and assessment of data science methodologies, utilisation of analytical tools, and exploration of big data analytics.
MODULES
- Applied Data Science
- Advanced Data Analysis and Visualisation
- Advanced Data Structures and Algorithms
- Advanced Machine Learning
- Database Systems and Data Analytics
- Research Methods for Digital Technologies
- Dissertation
Entry requirements & applying
Normal entry requirements for full time and part time will be one of:
- A Bachelor of Science Honours degree, normally 2:2 or above, in a relevant subject area for example Computing, Maths etc.,
- Academic qualifications in other subject areas or at a lower level than honours degree but supported by a maturity of experience at a professional level in a relevant specialist area.
- Equivalent qualifications of another overseas country which are deemed satisfactory by the program team.
Teaching & Assessment
Teaching
The computing program suite employs a diverse range of cutting-edge industry tools and software, complemented by innovative teaching methods. This dynamic approach not only imparts industry-relevant skills but also empowers you to elevate your work to new heights when possible.
Assessment
Assessments in Data Science and Big Data Analytics at university level are designed to evaluate your understanding, application, and proficiency in various aspects of the discipline. These assessments encompass a diverse range of methods, including:
- Coursework and Projects: Assignments and projects provide hands-on experience, allowing you to apply theoretical knowledge to real-world scenarios. This may include software development projects, research papers, or problem-solving tasks.
- Coding Assignments: Practical coding assignments assess your programming skills, logical reasoning, and ability to develop efficient and effective code.
- Group Projects: Collaborative projects evaluate teamwork, communication, and the ability to work in diverse teams, reflecting the collaborative nature of the tech industry.
- Presentations: You may be required to present your findings, solutions, or project outcomes, enhancing your communication and presentation skills.
- Laboratory Work: Practical sessions in computer labs assess your ability to apply concepts, troubleshoot issues, and work with various tools and technologies.
- Problem-solving Exercises: These exercises challenge you to solve complex problems, encouraging critical thinking and analytical skills.
- Reports and Documentation: Writing reports or documenting project processes assesses your ability to communicate technical information clearly and concisely.
Personalised Support
The department follows a well-established open-door approach, actively interacting with students, alumni, and industry stakeholders. Essential information and communication avenues are facilitated through tools like Teams and Moodle. Additionally, every student is assigned a personal tutor, fostering regular meetings, while additional personalised support is extended to part-time students through the Virtual Learning Environment (VLE).
Career prospects
One obvious advantage of a Data Science and Big Data Analytics master’s degree is that students become more employable. Jobs include, but are not limited to:
- Data Scientist
- Data Analyst
- Intelligence Analyst
- Machine Learning Engineer
- Big Data Engineer
- Predictive Analyst
- Research Scientist
Fees & funding
You do not have to pay your tuition fees upfront.
The fees you pay and the support available will depend on a number of different factors. Full information can be found on our fees & finance pages. You will also find information about what your fees include in the fee FAQs.
All fees are subject to any changes in government policy, view our postgraduate fees.
Programme specification
You can see the full programme specification here.Apply Now
This course is open to international students only. Please apply through our International Application System Centurus
