MSc Data Science
Manchester, United Kingdom
DURATION
1 up to 3 Years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
Request application deadline
EARLIEST START DATE
Jan 2025
TUITION FEES
GBP 17,550 / per year *
STUDY FORMAT
On-Campus
* full-time International students; Home students £9,990 per year; Part- time: £1,665 per 30 credits
Introduction
Make discoveries in data and bring value to businesses and organizations. With our Data Science postgraduate degree, you can enhance your existing computing knowledge, or gain new skills that can help you secure a role in one of the fastest-growing employment fields in the digital economy.
Developed as one of the UK's first data science postgraduate conversion courses, this Chartered Institute for IT (BCS) accredited degree will equip graduates and professionals from a wide range of disciplines, with analytical knowledge and applied programming skills.
Available with full and part-time study routes, our course will provide you with specialist data science knowledge to apply in a wide range of sectors, including healthcare, commerce, professional services, and the built environment. Start dates are available each January and September.
You will:
- Develop an awareness of the latest developments in databases, data mining, machine learning, and Big Data
- Work with real-world messy data and gain experience across the data science stack
- Broaden your mathematical aptitude as you explore 'Big Data', machine learning, and data visualization
Ideal Students
This is for You if...
- You want to enhance your existing skills and qualifications for a future career in data science
- You have an enquiring mind, with a practical and analytical approach to problem-solving
- You're a knowledge-seeker and want to learn how to tell a story with data
Curriculum
The course is delivered through a range of highly focused modules. The 180-credit MSc award comprises four taught modules, plus a research dissertation. The 120-credit PgDip award comprises four taught modules.
Flexibility is at the heart of our learning approach. You can choose to study this postgraduate course full-time or part-time on campus, with start dates in January and September:
- As a full-time student, you will complete modules in each of the first two trimesters and complete your 60-credit dissertation project in trimester three
- As a part-time student, you will complete taught modules in years one and two, and complete your dissertation project in year three
As part of your study preparations, you will be required to attend an intensive one-week session before formal teaching begins. This session will review basic statistics and database concepts, and provide an overview of either Python or R programming for data analysis.
The Data Science postgraduate course is delivered by an academic team with extensive industry experience and research connections, and a track record of developing solutions through industry partnerships.
Modules
- Advanced Databases
- Big Data Tools and Techniques
- Machine Learning and Data Mining
- Applied Statistics and Data Visualisation
- MSc Project
Career Opportunities
Demand for data scientists outstrips supply and there is continued demand for qualified professionals across many global industries.
As a data science graduate, you’ ll be equipped with the skill set and technical knowledge relevant to the data science and big data job market.
Further Study
You might also choose to take your subject interest further with postgraduate research. The Salford Innovation and Research Centre (SIRC) is home to Informatics Ph.D. and Research Master’s opportunities in knowledge discovery and semantic web, software engineering, big data, data mining and analytics, cyber security, information visualization and virtual environments.
Explore our Doctoral School to learn more about research training, support, and opportunities.
Admissions
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Program Admission Requirements
Show your commitment and readiness for Grad school by taking the GRE - the most broadly accepted exam for graduate programs internationally.