COVID-19 and the ensuing lockdowns accelerated the adoption and transition of pedagogical paradigms from a largely offline mode

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

The UNSSC “Innovation for Impact” e-Learning Path seeks to accelerate and foster innovation in the UN system by supporting capacity development to create greater impact and enhance the UN workforce's future resilience. The e-Learning Path is composed of the Introduction to Innovation Learning Module, and the UN Innovation Toolkit Learning Module, with the ambition to support innovation efforts in the UN at all levels by offering online learning that embraces the use of digital tools and innovation frameworks and approaches.

This self-paced course goes over some fundamental aspects of data literacy, explores the best ways to input and clean data to make it usable, and provides tips to put data in context through storytelling techniques.