The aim of this module is to provide a business deployment perspective of foundational Deep Learning AI capabilities, ranging from Natural Language Processing to Machine Vision; in a manner that requires little or no coding. Neural networks and how Deep Learning works, the data input requirements, project lifecycle, and the development framework would be introduced. What problems each specific AI algorithm can solve would be illustrated in an interactive workshop session and the enterprise benefits would be highlighted via case studies; e.g. enhanced productivity for corporate decision-making, process automation, or difficult unattended problem-solving.

The focus is on rapid prototyping and guiding the users and the relevant project team members to validate project viability using the data and requirements that are available. Importantly, you will gain the skills to highlight missing gaps, and failure scenarios and to discuss AI compliance, privacy, and cyber security requirements at the design phase, avoiding misunderstanding of the project’s complexity and hence be able to protect the project from failure.

Finally, modern challenges such as ensuring man-in-the-loop AI oversight, cyber security hardening against adversarial AI attacks, and privacy obligations would be covered as new requirements for an upgraded corporate IT risk management framework that will be instrumental in protecting the company’s digitalisation efforts.

The future of AI continues to shine brightly, and we aim to highlight major high-value factory automation future possibilities as AI and Big Data systems converge pervasively, and 5G and IoT AI at the edge become commodity. With these insights, you will master key leadership skills to manage and plan AI projects successfully and hence, deliver strategic benefits to the corporation.