Today, the interaction of digital technologies with daily routines isn't merely a passing trend but a fundamental shift, continuously redefining the possibilities and challenges in the world of work. This course aims to demystify AI and provides insights and skills on it thanks to a heterogeneous group of experts. They will explore AI's effects on training, knowledge management, and workforce development. They'll tackle key trends, and ethical considerations, and showcase innovative applications of AI that you can apply in your everyday life. Whether you're a student, educator, or professional, this Masterclass is your guide to staying relevant and succeeding in the evolving landscape of AI and education.

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.

C4D offers a practical experience focused on equipping participants with essential tools and strategies for effective communication within the development sector. It covers key aspects such as strategic communication planning, where participants will learn to design and implement communication strategies that align with organizational goals. Additionally, the course emphasizes storytelling and content creation, helping participants develop the skills to craft engaging, human-centered narratives that resonate with their audience. It also explores best practices for using both online and offline communication channels to maximize the reach and impact of messages. Participants will gain exposure to the latest trends and innovative approaches in communication for development, enabling them to apply creative solutions in their work and drive positive change in their respective fields.

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