Overview
The MSc in Data Science (Applied Urban Analytics) at The University of Manchester is an innovative programme that prepares students to become adept data scientists, ready to tackle the complexities of urban analytics. The University is consistently ranked among the top ten institutions in the UK for mathematics, statistics, and computer science, according to Times Higher Education 2024. This prestigious ranking reflects the university's commitment to academic excellence and its strong emphasis on research-driven teaching.
Why Data Science (Applied Urban Analytics) at The University of Manchester?Students benefit from the university's state-of-the-art facilities and a collaborative learning environment. The programme is designed to draw on various disciplines, enabling students to understand the vast potential of data in addressing urban challenges. The university also has strong ties with industry partners, ensuring that the curriculum is relevant and aligned with current market needs.
Tuition Fee BreakdownThe tuition fees for the MSc in Data Science (Applied Urban Analytics) are as follows:
- UK students: £16,500 per year
- International students: £33,500 per year
Visit the Fees and Funding section for a breakdown in your local currency.
SyllabusThe curriculum is designed to provide a comprehensive understanding of urban data science. Key modules include:
- Data Analytics and Statistics
- Computational Methods
- Urban Analysis Techniques
- Spatial Data Analysis
- Data-Driven Decision Making in Urban Policy
Students will engage in interdisciplinary projects that apply data insights to real-world urban settings, enhancing their practical skills and employability.
Careers with Data Science (Applied Urban Analytics)Graduates of this programme can expect to find diverse career opportunities across various sectors. Alumni have secured positions in urban planning, public policy analysis, and real estate market analysis. The skills acquired during the course prepare graduates for roles such as data analysts, urban data scientists, and GIS specialists, making them highly sought after in today's job market.
Programme Structure
Courses include:
- Programming in Python for Business Analytics
- Land and Development
- Real Estate Investment and Finance
- Advanced Real Estate Finance
- Property Valuation
- Applied Spatial Analysis for Planning
Key information
Duration
- Full-time
- 12 months
Start dates & application deadlines
- Starting
- Apply before
-
Language
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Credits
Delivered
Campus Location
- Manchester, United Kingdom
Disciplines
Data Science & Big Data Urban Planning Data Analytics View 114 other Masters in Urban Planning in United KingdomWhat students do after studying
Academic requirements
English requirements
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Other requirements
General requirements
- High 2:1 honours degree (or overseas equivalent)
For this pathway, we would expect applicants to evidence an interest and/or experience in topics related to urban analysis. Examples are:
- Working experience in urban-themed topics (e.g. data analyses for spatial phenomena, public policies or real estate market analysis)
- Experience in working in spatial or GIS-based data analysis
- Evidence of training in urban-themed methods or topics (e.g. GIS).
In your application, you should demonstrate aptitude, knowledge and/or interest in three areas:
- data analytics and/or statistics;
- computational subjects; and
- pathway specific requirements.
Tuition Fees
-
International Applies to you
Applies to youNon-residents33500 GBP / year≈ 33500 GBP / year -
Domestic Applies to you
Applies to youCitizens or residents16500 GBP / year≈ 16500 GBP / year
Living costs
Manchester
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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Scholarships Information
Below you will find Master's scholarship opportunities for Data Science (Applied Urban Analytics).
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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