AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone--especially your non-technical colleagues--to take. In this course, you will learn: - The meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science - What AI realistically can--and cannot--do - How to spot opportunities to apply AI to problems in your own organization - What it feels like to build machine learning and data science projects - How to work with an AI team and build an AI strategy in your company - How to navigate ethical and societal discussions surrounding AI Though this course is largely non-technical, engineers can also take this course to learn the business aspects of AI.

Frontier ICTs such as Artificial Intelligence (AI), Blockchain, and the Internet of Things (IoT) are expected to have a greater impact on sustainable development and are also recognized as an important source of concerns for socio-economic development (especially policymaking) in developing countries. Therefore, this module provides fundamental information, challenges/risks, best practices, policy recommendations, and international cooperation agendas related to frontier ICTs that digital leaders, in particular policymakers in developing countries, should consider when developing and applying the frontier ICTs to enable sustainable development through innovation in their public sector and society.

This course seeks to outline AI applications of particular relevance to peace and conflict settings from a gender perspective.

The Digital4Sustainability Learning Path explores the transformational role digital solutions and innovations can play in advancing environmental and social sustainability. In particular, how can digital technologies power the green transition, and how can the digital transition be green?