数据科学与分析理学学士学位（荣誉学位）-包括预科课程

预科课程 数据是我们社会的命脉。从医学到政府机关，再到市场研究再到环境，数据的收集和分析对于了解如何在全球范围内改善，创建和指导产品与服务至关重要。《哈佛商业评论》最近将数据科学家的工作描述为“ 21世纪最性感的工作”。数据科学涉及进行一些侦探工作并进行必要的调查，以指导重要的决策并预测新趋势。技术正在以惊人的速度增长和发展，我们生成的数据的增长速度以及用于处理技术的设备的增长速度都只能提高。
Data is the lifeblood of our society. From medicine to government offices, and market research to the environment, the collection and analysis of data is crucial to understanding how to improve, create and guide products and services across the globe.<br><br>Harvard Business Review recently described the job of Data Scientist as “the sexiest job of the 21st century”. Data science is about doing some detective work and carrying out the investigations needed to inform important decisions and to predict new trends. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.<br><br>Our BSc Data Science and Analytics (including foundation year) is open to Home and EU students. It will be suitable for you if your academic qualifications do not yet meet our entrance requirements for the three-year version of this course and you want a programme that increases your subject knowledge as well as improves your English language and academic skills.<br><br>This four-year course includes a foundation year (Year Zero), followed by a further three years of study. During your Year Zero, you study four academic subjects relevant to your chosen course as well as a compulsory English language and academic skills module.<br><br>You are an Essex student from day one, a member of our global community based at the most internationally diverse campus university in the UK.<br><br>After successful completion of Year Zero in our Essex Pathways Department, you progress to complete your course with our School of Mathematics, Statistics and Actuarial Science.<br><br>At Essex, we help you to understand how utilising the speed and processing-power of computers can assist in using data to make better decisions. You discover the new methods and the smart, unusual questions needed to make sense of both structured and unstructured data.