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.

More From the Library

ITU
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Building the digital economy: Pathways in Healthcare and Government

The first focus of this course is on the application, practice and development opportunities of AI in the healthcare industry, with a particular focus on the needs and realities of developing countries. It covers core AI technologies and their healthcare applications, practical paths for implementing AI healthcare projects in developing countries, and global trends and regional opportunities. Unique benefits include case studies tailored to developing regions, actionable implementation strategies, and insights into leveraging global resources for local development.
Short (a few hours)
Online
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UN Women
WHO
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Using Data to End Violence Against Women

Around one in three women worldwide experiences physical or sexual violence in their lifetimes. This stark statistic is powerful. It demonstrates the scale of the problem and the urgency of eliminating violence against women (VAW). But powerful data like this doesn’t come into being by itself; it’s the result of careful data collection and analysis around the world. In this free course
Short (a few hours)
Online
Data Innovation
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SDG 05: Gender Equality
SDG 16: Peace, Justice & Strong Institutions
UNSSC
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UN 2.0 Fundamentals E-Learning Path

As a service to the system, UNSSC has designed five, freely available, self-paced, introductory e-learning modules, each focusing on a cutting-edge skill identified in the Quintet of Change - UN 2.0 Policy Brief (Innovation, Strategic Foresight, Behavioural Science, Data, Digital).
Long (a few weeks)
Online
Behavioural Science
Strategic Foresight
Digital Transformation
Culture of Innovation
Data Innovation
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All
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)
Online
Generative AI
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All
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