The objective of this course is to build capacity among policymakers and stakeholders to better understand their science, technology, and innovation (STI) ecosystems and thus design and implement successful STI policies. The 2026 spring-summer session is closed for registration. The registration deadline was 20 February 2026. A new term and intake will be announced in Q4 2026.

AI is reshaping what is possible in learning design. This course helps you integrate AI into your creative process without sacrificing what makes your work valuable: empathy, insight, and human judgment. Developed by UNITAR's Learning Solutions Team, practitioners blending behavioural science, instructional design, strategic foresight, and ethical AI, it's a practical, human-centred learning experience built for real-world impact.

This course introduces participants to blockchain technology and provides a basic understanding of its main features. It begins by highlighting the business value of blockchain and the relevance of the technology for international trade. The lectures then move to explain the difference between blockchain and distributed ledger technology (DLT), defining key use cases for digital identity (ID), supply chain management, transportation / logistics, intellectual property rights, trade facilitation and financial services. The lectures further examine the opportunities blockchain / DLT may create for small producers and enterprises, especially those located in developing countries. Finally, the course explores the “blockchain for trade” ecosystem, implementation decision-making tools, regulatory requirements and other challenges that must be addressed before the technology can be used on a wide scale and generate significant impact.

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.