This MComp Honours course will prepare you to be a computing professional ready to work and succeed in this challenging and exciting industry.
The Data Science programme incorporates a number of distinct themes embedded in a solid framework of professional computing development. Major themes include; computer systems development, database design, development, warehousing and management, including advanced and distributed databases. Data Analytic aspects cover data discovery, cleansing, mining and visualisation. Advanced topics in big data, machine learning and predictive analytics are also covered.
The topics typically covered in this course include:
- Computer programming in Java
- Fundamentals of data science
- Database Development
- Data Warehousing, mining and visualisation
- Statistical modelling
- Big data, tools analysis and machine learning
- Advanced and distributed databases
- Applications development in big data and machine learning
On this course you will have direct access to experts in the field as well as state-of-the-art facilities at the University.
Please see guidance on core and option modules for further information on what you will study.
•Modules to introduce and develop effective computer programming skills to solve data science problems
•Learn the basics of how computers operate and how they can be grouped to form networks of ever-increasing size until we have the internet
•Learn how to use internet technologies to build effective web sites
•Learn the basics of database development
•Gain the fundamental knowledge needed to practice and apply data science techniques to everyday problems
•Lay the foundations of a successful professional career development path
Many of the themes introduced at level 4 continue to be developed throughout the remainder of the programme.
•A key theme in the Data Science programme concerns interactions with many types and forms of databases. Acquire database design, development and management knowledge and expertise
•Leverage this database experience to encompass data warehousing and database mining techniques as key data science skills
•Study statistical modelling as a basis for further exploration and application of data science and analytics topics
•Develop skills, knowledge and expertise in the effective presentation of data analytical exercises through data visualisation
•Develop research skills to enable innovative and effective applications of data science techniques and approaches and in preparation for the final year project
•Enhance career development by embedding a growing expertise in data science in a framework of industry standard professionalism
Sandwich degree students can undertake an appropriate year-long industrial placement.
•Develop expertise in advanced analysis of data applying machine learning techniques to data sets
•Build on previous expertise in database s by exploring cutting edge developments in advanced and distributed databases
•Explore and analyse '€œBig Data'€
•Apply data analytical expertise to effectively manage web and e-commerce enterprises
•Undertake a large individual project in the data science area of your choice
•Build on previous experience in machine learning to develop cutting edge predictive applications
•Apply machine learning techniques to Big Data
•Explore recent development in advanced and distributed databases
•Build on previous experience in research methods and apply those skills in the development of a large, individual research project in a student selected area of data science
Modules are designated as core or option in accordance with professional body requirements and internal Academic Framework review, so may be subject to change. Students will be required to undertake modules that the University designates as core and will have a choice of designated option modules. Additionally, option modules may be offered subject to meeting minimum student numbers.
Please see the programme specification document for further details on this course.
You will be assessed by a combination of coursework and exams plus an independent final year project which contributes substantially to your final mark. Your tutors will give prompt and constructive feedback via Canvas (our virtual learning environment), face-to-face or in writing. This will help you to identify your strengths as well as the areas where you may need to put in more work.
Application deadline details:
You'll have such a gret time at John Moores, you won't want to leave! Liverpool is a fantastic city to live in, really vibrant and it really feels like being at the heart of something. The Raz (or The Blue Angel to the uninitiated) is a great club. There’s also amazing shops and cafes down Bold Street, and there are loads of interesting societies to keep you busy. The uni is incredibly supportive, with a responsive SU and fascinating tutors who are always ready to help out with your studies.
Provisional for Year 1 for EU at £9,250
Provisional for Year 1 for England at £9,250
Provisional for Year 1 for Northern Ireland at £9,250
Provisional for Year 1 for Scotland at £9,250
Provisional for Year 1 for Wales at £9,250
Provisional for Year 1 for International at £14,000
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