Data in media education @HK

This is a growing list of data courses in media education @HK. It is currently sorted in alphabetic order of course code. News courses, revision of course details and suggeting formating/ styling are all welcome via Pull Request or email:


To add a new entry, please collect the following information:

  1. Course instructor
  2. Offering institution, course code and course title
  3. A brief introduction of the course (< 3 sentences)
  4. [optional] Course website
  5. [optional] Links of selected student projects
  6. [optional] Related learning resources you want to share


The catalogue is not an exclusive categorisation. It behaves more like "tag system". i.e. one course may appear in multiple list if one of its features matches the catalogue title. This section is also under development so please feel free to suggest/ comment/ fix things.


Data Literacy

Data Journalism


Research Design

Including conceptualization, modeling, coding, questionaire, sampling, ...

Web Scraping

Data Mining

Data Visualization

Information Design

Language & Software

Python language

R language




Data type

Social Networks and Social Media

Text mining

Time series

Geographical data

Web Design/ Web Development


Backend (data service)

Application domain


Social welfare

Environmental issues



Business, Finance and Economics

Full list

CDM3080 - Information Design Basics (@HKDI)

  • Instructor: Sannia HO / Terrance Chang

The aim of this module is to apply appropriate taxonomy to analyze, organize and categorize complex data with hierarchical clarity; interpret data graphically and systematically in a style which is easily understood; communicate the value of a message with the utilisation of words images; and apply color, space and form effectively to solve communication problems. In this module, students will learn a brief history of information design, basic taxonomy such as LATCH, explore visual hierarchy, visual mapping, apply visualization techniques in the graphical representation of data and information.

Program website

CDM4157 - Motion Graphic Studio (@HKDI)

  • Instructor: Yip Pak To / Terrance Chang

The aim of this module is to analyze the evolution & trends of motion graphics from pre-computer age to contemporary digital age; integrate the principles of visual communication and motion design in idea development and design production produce animation with 2D & 3D graphic elements, texts, and sounds; and create motion graphics works through a series of preproduction workflows. In this module, students will learn motion graphic trends, principle and applications, animation production skills, scripting, storyboarding and animatics. In this project, students are working with and Media company: The News Lens. The project is to produce a series of motion graphics for a workplace feature.

Program website

Student projects: on Behance

COM2116 - Audience Analytics and Media Strategies (@CityU)

  • Instructor: Dr Xiaofan LIU

This course aims to teach students the various approaches in audience analysis and the purposes, philosophies, and methods of obtaining audience information for different media, with a particular focus on Internet and social media. Strategies for developing and scheduling online campaigns will also be covered. Students are expected to gain a broad understanding of the different methods in measuring media, and the different parameters in evaluating media effectiveness. Students will engage in a group project to apply their knowledge and skills to develop action plans.

COM3117 - Media, Communication and Public Opinion (@CityU)

  • Instructor:

This seminar aims to describe, evaluate, and critique the literature on the role of mass media in public opinion formation and change. By the end of the semester, the students are expected to demonstrate the ability to evaluate research concepts and perspectives, and furthermore apply them to actual research projects.

COM3203 - Digital and Data Journalism (@CityU)

  • Instructor: Dr Xiaofan LIU

This course aims to train students to deliver a wide range of data-driven on-line journalistic works. It emphasizes a hands-on approach to practising data acquisition, data analysis, and the production of news content with multimedia data visualization.

COM3410 - Consumer Behavior Analysis (@CityU)

  • Instructor:

This course aims to provide students with the basic knowledge and understanding of the theories in psychology, sociology and anthropology, which are essential to the study of consumer behaviour. Student will be provided with the knowledge about psychology which is essential to the study of consumer behavior. Prevailing techniques of understanding consumers’ buying behaviours and business applications of consumer behaviour principles will be included.

COM5108 - Psychological Processing of New Media (@CityU)

  • Instructor: Marko Skoric

This course aims to discover and examine cutting-edge research in the areas of media psychology and new media studies. Specific topics addressed will include human-computer interactions (HCI) and computer-mediated communication (CMC) research on various types of new media interfaces such as the Internet, WWW, virtual reality, mobile media, and computer and video games.

COM5506 - Social Network Analysis for Communication (@CityU)

  • Instructor: Dr Chris Fei SHEN

The course covers basic theories and research methods of social network analysis, with a variety of applications for communication purposes. Specific topics include human interactions over online friendship networks (e.g., Facebook, Google+, etc.), information diffusion through microblogging websites (e.g., Twitter, Weibo, etc.), cross-national flow of media content (news, entertainment, advertising, etc.), word of mouth and viral marketing, contagious models for health communication, and etc. Students will learn how to design social network analysis studies, how to collect, integrate, analyse, and visualize social network data, and how to apply networking perspectives to solve real life issues in communication context.

COM5507 - Social Media Data Acquisition and Processing (@CityU)

  • (Guest) Instructor: Dr. Xinzhi ZHANG (Department of Journalism, Hong Kong Baptist University)

This course introduces the fundamental knowledge and hands-on skills on big data analytics and its application in media and communication. Special focus will be placed on Python programming, automated web data collection, and principles in analyzing, interpreting, and visualizing data. Technical details include, but not limited to, Python programming fundamentals, web scraping, web crawling, API, data storage, data processing, data exploration and preliminary analysis, text mining, social network analysis, and integrated data-driven storytelling.

Learning materials: @xzzhang2

Student projects: @xzzhang2

COM5508 - Media Data Analytics (@CityU)

  • Instructor: Dr Xiaofan LIU

The course trains students of communication and new media to analyze and visualize numeric, text, and visual data from social media using computational social science methods, tools, and algorithms. Students are expected to become proficient to select the appropriate and efficient methods to explore, analyse, validate, and visualize big data from social media for a variety of basic and applied research purposes such as theory-driven studies, data-driven reporting, news visualization, social media user recommender systems, and etc.

COM5961 - Data-driven Product and Services Design

  • Instructor: Prof. Bernard Suen

With the continuous development of the Internet to meet the growth of smart cities and the upcoming 4th industrial revolution, Internet of Things, Cloud Computing, Artificial Intelligence, Blockchain, and Big Data are increasingly being integrated into the fabric of our works and lives alongside mobile and social media. These technologies pose challenges to industries and organisations to adapt and to transform. The purpose of this class is to provide a framework for students to understand the context of this development, so they can equip themselves with required skills to prepare for a career in the field.

As smart, connected, and data driven products and services become more prevalent in this coming decade, knowing the sources of data and how to acquire them programmatically for further cleaning, filtering, aggregation, modelling, evaluation, visualisation, and on-demand interaction will become increasingly important. The class will focus on the UX/UI aspect of data driven product and service design with the goal of producing a Product Requirement Document (PRD), informed by qualitative and quantitative user research and front-end coded prototypes.

Course link:

COM5940 - New Media Business Model and Innovation

  • Instructor: Prof. Bernard Suen

In our present age of rapid technological disruption and business transformation, a sustainable innovation requires engaging user experience, robust technological infrastructure, and viable business model, the three critical factors for success. The purpose of this course is to prepare enrolled students in becoming data driven product/operation professional, digital marketing specialist, UX researcher/designer, and startup founder by helping them master the integration challenges of putting the three together.

Throughout the course, special emphasis will be given to new media project management in the context of lean startup, business model design and agile software development. As a sequel to com5961, the course will focus on the deployment of technology stack and back-end web services for supporting a cloud-based data driven product and business. This process will be guided by the SCRUM framework for iterative product releases and reviews.

Given the paradigm shift in computing, Machine Learning has become a core component in any data driven web service architecture. Building REST API backed by machine learning and deep learning models will also be a consideration to potential new media product or service. The CRISP-DM methodology introduced in com5961 will be used as a framework to guide data acquisition, exploration and modelling for supporting business innovation and new media product development.

Course link:

COMM3681 - Social Media Analytics for Communication Professionals (@CUHK)

  • Instructor: Dr. LIANG Hai

Web data collection (API + Scraping) and text mining basics with KNIME

Lecture notes

COMM5631 - Digital Humanities: Methods and Tools (@CUHK)

  • Instructor: Dr. LIANG Hai

Web data collection (API + Scraping), data management, data visualization, and text mining basics with KNIME.

Lecture notes

COMM6320 - Digital Research (@CUHK)

  • Instructor: Dr. LIANG Hai

Computational communication research, design, data collection, text mining, and advanced social network modeling with R programming.

Lecture notes

COMM7620 - Social Media and Online Social Networks (@HKBU)

  • Instructor: Tsang, Stephanie Jean

This course aims to familiarize students with both the practical and theoretical implications of social media-related technologies. Students will have first-hand experience of data mining, text mining, and online social network analysis.

Student projects and teaching materials: UXLab

COMM7770 - Data Visualization (@HKBU)

  • Instructor: Dr. WANG Ning

This course will introduce students to the field of data visualization. Students will (1) learn basic visualization design and evaluation principles, (2) be tutored on how to find and download datasets of interests, and (3) develop programming skills to create a good variety of common charts for effective data exploration and visualization. By the end of the semester, students are expected to become educated critiques of data visualization and comfortable programmers who are able to acquire, explore and visualize large datasets. They will also become familiar with the self-learning resources on R to continue to sharpen their skills beyond this course.

Guest lectures by Charlie Chen:

COMM7780 - Big Data Analytics for Media and Communication (@HKBU)

  • Instructor: Pili Hu

This graduate level course is an A-Z pathway for communication background students to start data driven reporting. The course includes Python foundation, web scraping, table manipulation, and 1-/ 2- dimensional analysis/ visualization. Open source, peer learning and reproducible reporting are also emphasised throughout the course.

Open source Python book

Student projects: F2018

ECON7910 - Data Visualization with Story-telling

  • Instructor: Pili Hu

This course teaches data visualisation based on the widely adopted Tableau software. No prior experience with data or programming skill is needed. The course will be self contained covering fundamentals of data and data processing pipeline, with a focus on visualisation. Students will have the opportunity to apply the visual story telling skills on economics, finance, and business datasets. The intended learning outcome is to become comfortable with high dimensional large datasets in the application domain, be proficient in building appropriate charts and be confident to tell stories with interactive dashboards. Each teaching session is organised into three segments: Theory; Self-paced/ instructor-assisted lab exercise; Feedback or sharing. Enrolled students will also be invited to a privileged MediaWiki site to find abundant curated materials, discuss with peers and contribute in an open source way.

IS4335 - Data Visualization (@CityU)

  • Instructor: Angela Lu/ Neil Cheung

In this course, we will explore ways to organize and derive meaning from vast amounts of data by using visual presentation tools and techniques. Students will learn concepts, methods, and applications of data visualization methods. The course will introduce interesting examples in different application areas. Students will also learn a spectrum of visualization tools from simple GUI-based packages such as Tableau, Excel, Pajek to more advanced programmable visualization packages in R language. They will be guided in creating engaging and interactive visualizations.

ITEC2016 - Data-Driven Visualization for the Web (@HKBU)

  • Instructor: Martin Choy

This course aims to equip our students with essential knowledge on web development and data-driven story-telling. On completion of the course, students should be able to develop and publish interactive data visualization on a website.

Student projects of F2018: 1 2 3 4 5 6 7

JMSC6116 - Social media analytics for journalists (@HKU)

  • Instructor: Prof. KW Fu

A brief introduction of the course (< 3 sentences) - This course is designed to provide training for master-level journalism or communication major students about the basic techniques of media data and social media analytics. It covers a variety of tools that help them conduct a range of applications including web scraping, API programming, text mining, sentiment analysis, network analysis, as well as data visualization. The course is designed and taught in problem-based or project-driven mode which aims to facilitate real life application of the techniques in a variety of media and communication settings.

Lecture notes: @fukingwa

JOUR2076 - Data Journalism (@HKBU)

  • Instructor: Roselyn Du

This entry level data journalism course is not just about dull statistics or dreary numbers. The aim of the course is to examine data journalism at its core through case studies and hands-on practice of data skills. Throughout the course, students will learn how to conceptualize, design, visualize, and produce data-based news stories using visualization tools. Students will end the semester by creating an interactive piece of data journalism.

Student projects: 1 2 3 4 5

JOUR2106 - Data Visualization for News (@HKBU)

  • Instructor: Pili Hu

This course trains our students with web based data visualization techniques, as well as a critical thinking and creative thinking mind with data. Students end the semester with a personal webpage and an online portfolio of data news. Key techniques are HTML, CSS, Javascript.

Student projects: S2017, S2018

JOUR3276 - Data Story Laboratory (@HKBU)

  • Offering institution: Data & Media Communication Concentration, Department of Journalism, HKBU
  • Course instructor: Dr. Rose LUQIU & Mr. Ho wa WONG

The course focuses on the practical exercise and integrated uses of different computational methods in data journalism and news reporting. Students will take part in the whole process of online news production.

Course website:

Sample student project:

JOUR7280 - Big Data Analytics for Media and Communication (@HKBU)

  • Instructor: Wang Xiaohui Vincent

This course aims to introduce the fundamental knowledge and hands-on skills of big data analytics in the field of media and communication. Special focus will be placed on techniques for searching, collecting, analyzing, interpreting, and visualizing data.

Teaching materials: @vincentwx

SDSC2004 - Data Visualization (@CityU)

  • Instructor:

Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines or bars) contained in graphics. This course introduces practical methods and tools to visualize big data to communicate complex information clearly and efficiently. Students will learn how to present, visualize, and communicate data in various forms clearly and concisely. The one mainstream data visualization tool will be covered in this class such as: Tableau, Qlikeview, Power BI, d3.js, Gephi, Weka, etc. The visualization in this course is mainly static graphics.

SDSC3001 - Big Data: The Arts and Science of Scaling (@CityU)

  • Instructor:

This course introduces students to an intermediate level of scalable data management and big data technology and effective visualization for data science. The students should have the foundations of C, Java or Python programming and database system as pre-requisites. The topics cover the scalable SQL and NoSQL data management solution, data mining algorithms, and practical statistical and machine learning concepts. The students will also learn how to visualize data and communicate results.

SDSC3011 - Social Data Processing and Modelling (@CityU)

  • Instructor:

This course provides students with an extensive exposure to the elements of data processing and modelling for social media. Topics include human error detection, missing data handling, record aggregation, data integration, categorical variable modelling, multivariate data modelling, multilevel data modelling, latent data modelling, temporal data modelling, and spatial data modelling.

SDSC3010 - Digital Trace Analytics (@CityU)

  • Instructor:

This course provides students with an extensive exposure to the elements of opinion/behavioural data analytics. Topics include self-reported data, behavioural data, social science sampling, questionnaire design, offline surveys, online surveys, digital trace measurement, multi-source data analytics, and privacy protection.

VAS4056 - Expanded Studies (Data Journalism) (@HKDI)

  • Instructor: Brian Lo

This module is focuses on studying the data explosion in the society as well as finding the way to make use of data with practical methods for journalistic reports and deliveries. Students are required to apply the use of data in journalistic storytelling with proper visual elements so as to deliver the message and produce evidence accurately to audience, listener and readers.

Recommended readings:

VAS4062 - Media Computer Graphic in Journalism (@HKDI)

  • Instructor: Raymond Yau

The module introduces the practical skills and use of tools for information design and graphic communication from its inception and concept development to its completion. Students can learn and apply the visual languages and graphical skills for producing information based news stories as well as publishing and broadcasting in journalism aspects.