This course discusses building inclusive and digitally accessible environments and communities, underlining the importance of digital inclusivity and accessibility for all people, empowered through ICTs regardless of gender, age, ability, or context.

This annual Innovation Fellowship builds the innovation skills and competencies of people from both within and outside the UNHCR community, making innovation understandable, accessible, and applicable to our everyday work.

This module aims to build the ability of an Information Management Officer (IMO) to analyse data. It explores the steps involved in data analysis, creating data analysis plans, organizing and summarizing data, and understanding linkages between clusters.

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