SDSC1001 - Introduction to Data Science | ||||||||||
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| * The offering term is subject to change without prior notice | ||||||||||
Course Aims | ||||||||||
Data is everywhere. This is the first introductory course for the first-year students without backgrounds in college mathematics or statistics or computer programming. The course aims to provide the training of the important mind-set and unique perspective of data-driven modelling: how to identify, formulate, process and interpret the role of data and data techniques when modelling the real problems. In this course, we will describe the roles of data analytics in solving various scientific, engineering, business, societal problems, by presenting a large set of empirical case studies and successful applications across various industries. This course will be co-taught by multiple lecturers on selected topics related to the data science from the traditional applications to the most state-of-the-art industrial applications. Rather than developing abstract and specific theoretical knowledge, the focus of the course will be the overview of the data science and the participation of versatile projects and applications from real world. Through interaction with guest lecturers, pilot group projects and individual written reports and oral presentations, students will gradually build up the unique viewpoints of data resource behind many successful businesses and the understanding of the vital functions of big data in modern societies. | ||||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||||
Continuous Assessment: 80% | ||||||||||
Examination: 20% | ||||||||||
Examination Duration: 1 hours | ||||||||||
Note: To pass the course, apart from obtaining a minimum of 40% in the overall mark, a student must also obtain a minimum mark of 30% in both continuous assessment and examination components. | ||||||||||
Detailed Course Information | ||||||||||
| SDSC1001.pdf | ||||||||||
