A collaborative effort of UNDP’s Sustainable Finance, Climate and Energy teams, Introduction to Sustainable Finance for Climate and Energy is the first free online course to introduce critical concepts in climate and energy finance to a global audience. This course provides learners with concrete tools for financing climate and energy targets, including sovereign debt instruments (green bonds, blue bonds, debt-for-nature swaps), carbon markets, and innovative private finance solutions – underpinned by Integrated National Financing Frameworks (INFFs). The course also provides a foundation for measuring impact on climate and energy targets (IMM), and for de-risking sustainable investments in climate and energy.

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

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.

This learning path begins with an introduction to UN 2.0, followed by an exploration of the five cross-cutting competence areas—known as the Quintet of Change. You'll start by building a solid foundation with LinkedIn courses that showcase how these competencies are applied in today’s business world. Next, dive deeper into each area with advanced sub-learning paths. These include high-level LinkedIn courses from which you can understand how you can build that cross-cutting competence into your work area. This is accompanied by key UN materials, essential policies, strategies, and tools. Finally, the journey concludes with a curated collection of UNICEF’s most valuable learning resources.