Brand, product, and service crises can be catalysed and magnified by collective opinion on the Internet. Such marks the age of doing business on the Internet, where online crises can develop in the blink of an eye.

The most common type of data breach is ransomware. Such attacks are usually publicised and widely known, causing untold harm to a business’ reputation. This is because ransomware threat actors usually publish their successful compromise of their victims, in order to gain more leverage to force their victims to pay the ransom demands. In addition, ransomware attacks can cripple the operations of a business, adversely impacting the delivery of goods and services to the business’ clients.

The rise of social media has resulted in polarising opinions, differing experiences and general feelings of uncertainty and anxiety. People turn to social media to vent, criticise, seek solace and garner support. Opinions can change, and the tides of online reputation can turn in a matter of hours. Brand, product, and service crises can be catalysed and magnified by collective opinion on the Internet.

Once negative information hits the web, it can be difficult to remove. So what should you do if your business suddenly experiences an uptick in negative reviews, faces a social media crisis, or worse?

No matter your industry or size of your company, there has never been a bigger need than today to protect and improve your online reputation. When customers or ex-employees leave your company a negative review, your brand's online reputation can go sour very quickly.

This module provides participants with an understanding of data governance in today's digital and regulatory environment using the ISO/IEC 38505 standard. In the post Covid-19 world, digitalisation and data will play a bigger role in accelerating business recovery and driving decisions. Therefore data management will be key. The ASEAN Data Management Framework provides businesses with guidelines for their data governance structures and management of data.

Imagine living in a world of virtual reality, where one dives into a virtual world, interacting with your friends from the real world in the virtual space. Such may seem a highly unrealistic dream scenario, conjured by deluded groups of people. However, just like how out of the question the concept of the Internet was in the 1980s, the Metaverse might not be as unthinkable as we thought. This course will allow participants to demystify the Metaverse, deepen their understanding, learn about its applications and business opportunities.

This is a sequential programme and is not available on a standalone basis.

Python programming language has become increasingly popular for algorithmic trading, where financial instruments are traded using rules or algorithms with little or no human intervention.

In this course, uncover the mechanics of process-driven investing, learn to extract historical stock data using Python, and formulate based on historical data theory-driven and data-driven trading strategies.

This module is part of a sequential programme and is not available on a standalone basis.

In this course, participants will learn when business analytics require causal inference, and why it's crucial for. They’ll learn how to execute causal analysis in Python and interpret the results. Additionally, participants will also explore the logic of causation, A/B testing fundamentals, and econometric methods for analysing causality in naturally occurring data. 

This module is part of a sequential programme and is not available on a standalone basis.

Machine learning (ML) is one of the most effective methods for forecasting CLV, as it uses past data to predict future customer behavior. This empowers organisations to fine-tune their marketing strategies, optimise campaigns and allocate resources more effectively.