This course provides a comprehensive overview of sustainable urban mobility, covering topics such as urban mobility policies, financing strategies, low-carbon mobility solutions, and the role of data, innovation, and technology in enhancing urban mobility.

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

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.

The course builds upon the Inclusive Digital Economies and Gender Equality Playbook