This 2-week online course equips UN analysts and data practitioners with practical skills to systematically assess and improve data quality using Python.

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

Our goal is to demystify AI The Elements of AI is a series of free online courses created by MinnaLearn and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.

The amazing potential and opportunity of Generative AI has also brought ethical concerns. How can you address these concerns effectively as you deploy tools and products powered by generative AI? In this course, expert Vilas Dhar equips designers and decision makers to better understand and act on the emerging ethical risks and considerations of generative artificial intelligence. Get a solid introduction to the ethical concerns around generative AI, then learn how to use a framework of ethical analysis to address these concerns. Plus, explore ways you can prepare your organization to address ethics in AI across all stakeholders from technology to C-Suite leaders.