The programme aims to produce data-analytic and business-aware graduates to meet the growing demand for high-level data science skills and to prepare graduates to apply data science techniques to knowledge discovery and dissemination in organizational decision-making. It is also intended to help established data analytic professionals upgrade their technical management and development skills and to provide a solid path for students from diverse fields to rapidly transition to data science careers.
港城大offer周末3连击- 数据科学
- 原创
背景介绍
申请难点
留学规划与提升
院校解读
留学方案
案例分析
申请心得： 印象非常深刻的是学生来咨询的时候，表达了对本专业非常不喜欢的态度，想学一些实用性更强的专业。 考虑到本身学生理工科的背景，除了本专业外，给学生建议了 数据，运筹等专业，由于数据类分析类专业是听热门的专业，所以我们一直等待录取，等了有半年多，过程中有本专业录取也是意料之内的， 但现在6月了拿到数据专业录取，学生还是表示愿意转去读。
香港城市大学在21年QS的排名中挤入了全球50名内，
学生入读的数据科学系介绍如下：
Programme Aims and Objectives
Entrance Requirements
Applicant must be a degree holder in Engineering, Science or other relevant disciplines, or its equivalent
Non-local candidates from an institution where medium of instruction is not English should fulfill one of the following English proficiency requirements.
- a score of 550 (paper-based test) or 59 (revised paper-delivered test) or 79 (Internet-based test) in the Test of English as a Foreign Language (TOEFL); or
- an overall band score of 6.5 in International English Language Testing System (IELTS); or
- a minimum score of 450 in band 6 in the Chinese mainland’s College English Test (CET6); or
- other equivalent qualifications
Fellowships Scheme
Fellowship awards are available for local students admitted to this programme under the Fellowships Scheme supported by the HKSAR Government. This programme in the priority area of “Research and Innovation” is one of the targeted programmes listed under the Fellowships Scheme with 9 fellowship awards. Local students admitted to the programme in full-time, part-time or combined study mode will be invited to submit applications for the fellowships.
Course Description
Core Courses (15 credit units)
- Exploratory Data Analysis and Visualization
- Research Projects for Data Science
- Statistical Machine Learning I
- Statistical Machine Learning II
- Storing and Retrieving Data
Electives (15 credit units)
- Bayesian Data Analysis
- Data Analytics for Smart Cities
- Dynamic Programming and Reinforcement Learning
- Experimental Design and Regression
- Information Security for eCommerce
- Machine Learning
- Machine Learning at Scale
- Natural Language Processing
- Optimization for Data Science
- Privacy-enhancing Technologies
- Storing and Retrieving Data
- Time Series and Panel Data
Remarks: Course offering is subject to sufficient enrolment.
