AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone--especially your non-technical colleagues--to take. In this course, you will learn: - The meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science
- What AI realistically can--and cannot--do
- How to spot opportunities to apply AI to problems in your own organization
- What it feels like to build machine learning and data science projects
- How to work with an AI team and build an AI strategy in your company
- How to navigate ethical and societal discussions surrounding AI Though this course is largely non-technical, engineers can also take this course to learn the business aspects of AI.
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Artificial Intelligence for Learning Professionals
AI is reshaping what is possible in learning design. This course helps you integrate AI into your creative process without sacrificing what makes your work valuable: empathy, insight, and human judgment. Developed by UNITAR's Learning Solutions Team, practitioners blending behavioural science, instructional design, strategic foresight, and ethical AI, it's a practical, human-centred learning experience built for real-world impact.
Short (a few hours)
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Data Analysis
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.
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SDG 09: Industry, Innovation & Infrastructure
UNCTAD
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The Use of Blockchain in Trade Facilitation
A course about the pivotal role that blockchain is having and will have in trade facilitation. Discover how this technology, alongside digitalization and automation, optimizes supply chain efficiency.
Short (a few hours)
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SDG 09: Industry, Innovation & Infrastructure
Other
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Generative AI Prompt Engineering Guide
Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.
Motivated by the high interest in developing with LLMs
Medium (a few days)
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Culture of Innovation
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Frontier Technologies
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Join the UN Innovation Network
Thanks for your interest in joining the UN Innovation Network (UNIN). UNIN is a network for UN employees interest in innovation; we welcome non-UN colleagues in an observer role.
To get to know our members, their skills and expertise better, we would like to ask you a few questions about your work and interests. Please complete this form to reflect your own experiences and interests, not those of your team or organisation.
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