University of St Andrews Data-Intensive Analysis (MSc) 세인트앤드루스 대학교 데이터 분석학 석사

The MSc in Data-Intensive Analysis is an interdisciplinary course providing students with an understanding of how data is used to gain useful insights in all areas of scientific endeavour. The programme has a substantive statistical component – both theory and practice – allied to computational data science and visualisation.

 

Course type : MSc

Course dates

• Start date: 5 September 2022
• End date: 30 September 2023

Entry requirements

• A 2.1 Honours undergraduate degree, plus evidence of some previous programming experience in an object-orientated language (for example, Java). -> 프로그래밍 관련 과목 3.5/4.5 or 3.0/4.3
• English language proficiency. See English language tests and qualifications. ->overall 7.0 component 6.0

 

Modules

Compulsory

• Introductory Data Analysis: covers essential statistical concepts and analysis methods relevant for commercial analysis.
• Advanced Data Analysis: covers modern modelling methods for situations where the data fails to meet the assumptions of common statistical models and simple remedies do not suffice.
• Knowledge Discovery and Datamining: covers many of the methods found under the banner of "datamining", building from a theoretical perspective but ultimately teaching practical application.
• Applied Statistical Modelling using GLMs: covers the main aspects of linear models and generalized linear models, including model specification, various options for model selection, model assessment and tools for diagnosing model faults.

Optional

• Computing in Statistics: teaches computer programming skills, including principles of good programming practice, with an emphasis on statistical computing. 
• Software for Data Analysis: covers the practical computing aspects of statistical data analysis focusing on widely used packages, including data-wrangling and visualisation.
• Data-Intensive Systems: presents the programming paradigms, algorithmic techniques and design principles for large-scale distributed systems, such as those utlised by companies such as Google, Amazon and Facebook.
• Information Visualisation and Visual Analytics: explores how to utilise visual representations to make information accessible for exploration and analysis.
• Masters Programming Projects: reinforces key programming skills gained during the first programming module of the programme and offers increasing depth and scope for creativity.
• Object-Orientated Modelling, Design and Programming: introduces and reinforces object-orientated modelling, design and implementation to provide a common basis of skills, allowing students to complete programming assignments within other MSc modules. 
• Programming Principles and Practice: introduces computational thinking and problem-solving skills to students who have no or little previous programming experience.