CS105 Statistical Thinking for Data Science
Term(s) taught: 2019/20 Term 2, 2020/21 Term 2
This is an introductory course in probability and statistics. It lays the mathematical foundation to prepare the students for computer science courses and their applications, in particular data science and related areas such as machine learning and artificial intelligence. The main topics covered in this course include probability, random variables, limit theorems, statistics, regression and inference, coupled with hands-on activities to illustrate their relevance to data science. Thus, the course will require both the understanding and development of some theoretical results with mathematical rigor, as well as some first-hand experience on practical applications.
ISSS606 Social Analytics and Applications
Term(s) taught: 2018/19 Term 2 & 3, 2019/20 Term 2 & 3, 2020/21 Term 2
This course focuses on data analytics in the context of social media. Increasingly people interact with each other on social media on a daily basis, which generates a huge amount of social data. We are primarily interested in two types of social data: social relationship networks, such as friendship networks and professional networks, and social text data such as user reviews and social status updates. Thus, this course integrates both network (formally known as graph) mining and text analytics, with more emphasis on the network portion. This course will prepare you with the fundamental data science and programming skills to process and analyze social data, in order to reveal valuable insights and discover knowledge for making better decisions in business applications. You will not only learn the different theories and algorithms for social data analytics, but also have a chance to apply them to real-world problem solving through in-class lab sessions and course project.
IS111 Introduction to Programming
Term(s) taught: 2018/19 Term 1
An introductory course for programming, using Python as the exemplary language. Basic programming concepts and constructs, such as variables, containers, functions, control flow etc. No prior knowledge in coding required.