溫切斯特大學(xué)

- Prepare for the information challenges of the future with cutting-edge data modelling and analysis. - Opportunity to use specialist data analysis software and a wide range of databases- Develop a range of skills in business analytics, computer science and data managementFrom online shopping and social networks to scientific research and finance, we collect immensely detailed information. Data Scientists are concerned with turning this data into intelligence through the application of cutting-edge techniques in Computer Science and Statistics . Data science is an interdisciplinary field combining methods, processes, algorithms and systems to extract knowledge or insights from data.The modern business world increasingly requires a higher level of data science expertise as well as abilities in problem solving and data analytics. This programme provides the opportunity to develop your knowledge, understanding, technical skills and confidence to operate successfully in a globalised work environment. It integrates key themes in quantitative data analysis, information management, predictive analytics, strategic forecasting, insight management and business intelligence.You will have access to a wide range of databases for research purposes as well as specialist data analysis software, developing your project skills in various ways. Advanced modules may include topics such as Predictive Data Analytics, Visualisation of Business Intelligence and Insight Management. In Year 1 you will be introduced to academic study at Level 4 and the different core areas required of Data Scientists including Quantitative Data Analysis, Cyber Security and Database Design. Year 2 will build on the foundations of Year 1, including a group project. After Year 2, there is the opportunity for a work placement in Computing. Throughout Year 3 you will pursue an individual data science project, culminating in the production of a substantial project report.Graduates in Data Science may find careers in a multitude of industries with roles such as data scientist, software developer, IT project manager, IT consultant or computing researcher .