The modules delivered under the course provide a blend of technical skills and soft skills with an aim to strengthen both digital and inter-personal skills of girls and young women. The course prepares participants to actively engage in Science, Technology, Engineering and Mathematics (STEM) related initiatives and future career opportunities in the digital sector. It provides a practical approach with scenarios and case studies that foster innovation and creativity for continued learning on the use of digital technologies and how they can contribute to the digital ecosystem.

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UNDP
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Digital Fitness Programme

The Digital Fitness Programme (DFP) is a hands-on digital product design and management training for talented Operations and Programme Managers aiming to built and roll out digital solutions.
Medium (a few days)
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UN Habitat
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Taking sustainable urban mobility to the next level (Part 1)

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.
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SDG 11: Sustainable Cities & Communities
UN Tourism
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Tourism Innovation

Tourism Innovation is your gateway to understanding essential concepts in tourism innovation, offered as a four-week online course by Externado University of Colombia. You will explore sector guidelines, legal frameworks, and the tourism value chain. This course helps you integrate new practices for sustainable development and enhance your competitive edge. Engage with text, videos, and quizzes, and achieve an 80% score on the final quiz to earn your certificate.
Long (a few weeks)
Online
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SDG 09: Industry, Innovation & Infrastructure
Other
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Generative AI with Large Language Models

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
Medium (a few days)
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