As a public servant (and human), each day you’re likely to be faced with a mountain of decisions, ranging from miniscule to massive. Have you ever wished that you could make those decisions just a little bit easier, and just a little bit more effective? If so, you’re not alone — and this course can help get you on the right track. In this course, developed in collaboration with UN colleagues, including the UN Innovation Network (UNIN), you’ll dissect the decision-making process and determine what makes decisions so difficult, what makes some decisions more difficult than others, and what you can do about it. By the end of this course, you will be able to: - Recognise what makes decisions challenging and why it matters - Understand how personality influences decision-making - Identify common behavioural biases and strategies to overcome them - Dissect difficult choices and help others make the right call

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.

This course gives aspiring young entrepreneurs a clear understanding of the path of entrepreneurship, the risks and rewards of being an entrepreneur, as well as the business start-up process. Young men and women will benefit from enhancing their entrepreneurial mindset and developing skills to identify and act on opportunities. It takes you through the main concepts behind innovation, allowing you to understand how innovation adds value to your business, why it is important to consider it in your strategy, and how to operationalize it. As an entrepreneur, you probably have heard a lot about innovation, especially if you are working with digital technologies. However, Innovation is not only a concept that fits the digital world, it is a process that places the needs of the customer at the centre of any offering.

By taking this course, you'll learn to: - Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection, to performance evaluation and deployment - Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases - Use empirical scaling laws to optimize the model's objective function across dataset size, compute budget, and inference requirements - Apply state-of-the art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project - Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners