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

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).

This learning path begins with an introduction to UN 2.0, followed by an exploration of the five cross-cutting competence areas—known as the Quintet of Change. You'll start by building a solid foundation with LinkedIn courses that showcase how these competencies are applied in today’s business world. Next, dive deeper into each area with advanced sub-learning paths. These include high-level LinkedIn courses from which you can understand how you can build that cross-cutting competence into your work area. This is accompanied by key UN materials, essential policies, strategies, and tools. Finally, the journey concludes with a curated collection of UNICEF’s most valuable learning resources.

This course focuses on technical, business and regulatory aspects of Internet of Things (IoT), Big Data and Artificial Intelligence (AI). It covers Internet technologies for IoT, then IoT standards, architectures and interoperability, as well as IoT policies and regulations, including IoT security and privacy issues. The course includes IoT services in 4G and 5G mobile systems, including massive IoT and critical IoT use cases. The IoT generates large amounts of data that cannot be processed by traditional techniques, and such data is referred to as Big Data. In that manner, the course includes Big Data overview, Big Data ecosystem and reference architecture, Big Data technologies and use cases, as well as business and regulatory challenges for Big Data. Artificial Intelligence (AI) is targeted for processing Big Data in Internet and telecom networks. In that regard the course covers introduction to AI in ICT/telecom world, and AI applications in Internet and telecom environments, including Machine Learning aspects for 5G mobile networks. The course further includes Big Data and AI challenges, business aspects, as well as policies and regulation. Finally, the course covers governance of IoT, Big Data, and AI.