17 - 21 April 2023 | every morning 10:00 - 12:00 and afternoon 14:00 - 15:30 SAST

Facilitator: John Stuart, tralac Associate

Background

The deluge of data generated by online activities and activities involving devices and the internet of things (IOT) has led to the growth of a new area of specialisation entirely dedicated to the effective usage of this data. ‘Data Science’ refers to the practice of acquiring, analysing and communicating insights from data, with the primary purpose of generating actionable insights to the solving of problems. The obvious example is that of an e-commerce business wishing to acquire insights on how better to market products to its customers, but the same tools are used to generate solutions to medical, biological, agricultural, security-related and geoscientific problems too (among others). Late in 2022, the OpenAI foundation released its ‘ChatGPT’ interactive AI bot to the public and the reaction has been nothing less than spectacular. Yet this advanced technology is based on the same basic machine learning techniques at the core of data science.

While generally not requiring the technologies related to ‘big data’, trade analysis can benefit substantially from the other cornerstone of the data science field – statistical learning. These techniques (known as ‘machine learning’ when applied on modern high powered computers) can reveal accurate predictions and inference around many of the problems that trade analysts are required to solve.

The Trade Law Centre (tralac) is an NPC focussed on trade, trade and industrial regulation and economic integration in Africa. In order to help trade analysts and economists come up to speed with the new technology, tralac is offering a one-week introductory e-Learning course to the techniques and methods of data science. This course will help orientate students around the new practices, tools and terminology. The course will be applied in the sense that the students will be required to complete exercises during the learning process, as well as a small project with results presented on the final day. The course will introduce, but not require coding for completion; rather the data science workflow will be completed using the Knime Desktop Analytics Platform.

Course Outline

pdf 2023 tralac Data Science Short Course Outline (236 KB)

Requirements

• This course is intended for practitioners who already work with, and analyse data using tools such as Microsoft Excel. No pre-training is provided on MS Excel or on basic data analysis.

• All participants must possess their own Windows laptop computer, which should be a recent model and should have at least 4GB of RAM and around 2GB of usable storage space for software and data. Students need to have administrator rights on this laptop (i.e., the right to install new software).

• In order to participate, the free Teams webinar platform is required to be installed on the participants’ laptops; access to the free Google Drive service is also required.

• Required reading: the Knime Beginner's Luck (sample)

To Apply

1. Email a brief motivation to This email address is being protected from spambots. You need JavaScript enabled to view it. where you describe how you are currently working with data, why you wish to learn about Data Science techniques and what you intend to get out of the course.

2. Complete this evaluation form to demonstrate your understanding of the required reading - the Knime Beginner's Luck (sample)

Closing date: 31 March 2023