In today’s rapidly evolving world, we face unprecedented societal challenges – social and economic inequality, climate change, unemployment, and technological disruptions, among others. These complex issues call for critical thinking perspectives and innovative solutions. Against this background, social innovation stands out as a crucial catalyst for addressing these challenges and fostering new strategies and sustainable solutions that traditional methods often overlook.

Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools. Motivated by the high interest in developing with LLMs

Big data and data analytics emerged quickly in the past decade and they aren't buzz words; they are a reality and they are all making an impact in education. Learning analytics are becoming essential for data-driven decisions in education. A key component of the future of learning institution, as they are used to optimize learning environments for students and employees. The data generated by digital learning ecosystem can guide training managers in making informed data-driven decisions, and students seeking for a personalized learning experience. By taking this course you will learn how to make data-driven decisions to optimize learning and the environments in which it occurs. The course is designed to increase your understanding of learning analytics and it will prepare you to make data-driven decisions about education improvement using a broad range of data collection, analytical, and visualization methods.

Digital Agricultural Technologies (DATs) are innovations that enable farmers and agribusiness entrepreneurs to leapfrog to increase their productivity, efficiency, and competitiveness, facilitate access to markets, improve nutritional outcomes and enhance resilience to climate change. These technologies range from mobile apps to digital identities for farmers to solar applications for agriculture to portable agriculture devices. DATs are increasingly becoming indispensable in the global food and agriculture sector, from fast and convenient information delivery to providing virtual marketplaces. Considering the fact that digital technologies can accelerate agro-food outcomes is juxtaposed with low adoption rates of the same, the World Bank’s operations are increasingly incorporating digital agriculture as a critical element in its operations. Thus, it is important to study digital agriculture technologies in further detail. This five-week course will provide a high-level overview of DAT concepts, potential impact, range of technologies available, used cases as well as forward-looking technologies. The course will introduce the participants to different agriculture data platforms already available and will encourage them to discover the scope and utility of the open data platforms for analytics and intelligence in agriculture. Participants will be required to engage in discussion forums with their peers and complete quizzes throughout the course.