Data Science (International) MSc
Postgraduate
In London
Description
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Type
Postgraduate
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Location
London
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Duration
2 Years
The Programme is built around a combination of Data Science programmes offered separately by both UCL and UniSA. Modules delivered by UCL for the Programme focus on theory, whilst the UniSA modules are comparatively more practical. Students benefit from the combination of theoretical and applied data science, with practical training and a final real-world project undertaken at UniSA.
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Start date
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About this course
Enter the revolutionary area of big data where there is an acute shortage of data scientists. A McKinsey Global Institute report forecasts a 50 per cent gap between projected demand and supply by 2018.
In the UK, the big data and artificial intelligence boom is expected to generate 56,000 data science positions from 2016-2020.
While the demand for analytic skills crosses multiple industries, fields such as marketing, health care, IT, government and finance are expected to experience a particularly strong need for analytics professionals
A minimum of an upper second-class Bachelor's degree in a quantitative discipline from a recognised UK university or a non-UK qualification of an equivalent standard in a relevant discipline typically in the fields of mathematics or computer science. Students should be comfotable with a high level of programming in a language such as Python.
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Subjects
- Data science
- Science MSc
- Data Science MSC
- Web Economics
- Research methods
- Machine Vision
- Graphical Models
- Data Mining
- Techniques
- Data Visualisation
Course programme
The aim of this programme is to produce graduates with the analytic and technical skills to effectively use Python, Hadoop, R and SAS to analyse Big Data and extract useful information to support the management and operations of an organisation.
You will undertake modules across a broad range of data science topics, which will provide you with hands-on experience in data analytic techniques for real-world challenges.
Taught by leading researchers in data science, you will learn to analyse and visualise rich data sources, spot data trends and to generate data driven insights.
Students undertake modules to the value of 240 UCL Credits (72 UniSa Units).
First year (UCL)120 UCL credits/36 UniSA units, comprising 4 compulsory modules (60 credits), 4 optional modules (60 credits) (UCL system). Second year (UniSA) 120 UCL credits/36 UniSA units, comprising 4 compulsory modules (2 x 4.5 units, 2 x 9 units (thesis), 2 optional modules (2 x 4.5 units) (UniSA system).
Core modules- Introduction to Deep Learning
- Introduction to Machine Learning
- Applied Machine Learning
- Data Analytics
- Statistical Programming for Data Science
- Unsupervised Methods in Analytics
- ITMS Masters Minor Thesis 1
- ITMS Masters Minor Thesis 2
- Graphical Models
- Machine Vision
- Information Retrieval & Data Mining
- Statistical Natural Language Processing
- Web Economics
- Advanced Deep Learning and Reinforcement Learning
- Research Methods
- Advanced Analytic Techniques 1
- Advanced Analytic Techniques 2
- Data Visualisation
Students who have not previously studied research methods should include the course Research Methods as one of their choices.
Subject to Programme Director approval, and the availability of an appropriate project and supervisor, students may elect to undertake their project over two semesters by enrolling in COMP 5005 in their first semester in Adelaide. In this case, they should also seek advice from the Programme Director on their choice of electives.
Dissertation/reportThere will be two minor theses as part of this programme, each thesis comprising one 2 hour lecture and 13 weeks of directed study. Students are then expected to present a 20-minute research seminar and submit a research report as a minor thesis, of approximately 9000 words. The proportion of total assessment of these last two components is as follows: Seminar – 10%; Research report – 90%; the two courses are ITMS Masters Minor Thesis 1 and ITMS Masters Minor Thesis 2.
Data Science (International) MSc