Facilitators: Vincent Ng (COMP), Rufus Huang (COMP)
Date: 18 Oct 2017
Time: 12:30 PM - 1:30 PM
Venue: TU616

In this two-session workshop series, essential concepts and procedures of performing student data analysis will be introduced. Python, the most popular programming language of IEEE Spectrum 2017, will be used in this workshop series with a widely used code editor, Jupyter Notebook.

The first session will introduce some basic features of Jupyter Notebook and how it works with common data files such as Excel files and csv files. A sample dataset will then be used to illustrate various data visualization functions and machine learning techniques for exploring student learning behaviors. The second session is a hands-on session for participants to explore the functions introduced in the first session. Sample datasets will be provided and colleagues can bring their own laptops to experience the power of Jupyter.

*This seminar is jointly organised by EDC and the CoP on Conducting Learning Analytics to Inform Teaching and Learning.