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

WFP aims to integrate a human-centred design approach into all the technology solutions it develops. When it comes to large and complex organizations like WFP, a human-centred design approach involves ensuring that all services are designed well with the user at the centre. This training course will give you an understanding of the human-centred design approach, where service design comes in, why it is so valuable, and how it can be applied in an organization like WFP.

The course is Intended for policy-makers, decision-makers, innovators and ecosystem builders who wish to build thriving entrepreneurial communities that can navigate technological revolutions and create competitive ICT industries. The course introduces key terminologies, concepts, tools and steps to assess your country's innovation capacity through practical information. Upon completion of the course, you will understand: Innovation, digital ecosystems and digital transformation, and their relationship to national development priorities.

During this 8-hour deep dive, you will be introduced to the key techniques, services, and trends that will help you understand foundation models from the ground up. This means breaking down theory, mathematics, and abstract concepts combined with hands-on exercises to gain functional intuition for practical application. Throughout the course, we focus on a wide spectrum of progressively complex generative AI techniques, giving you a strong base to understand, design, and apply your own models for the best performance. We’ll start with recapping foundation models, understanding where they come from, how they work, how they relate to generative AI, and what you can to do customize them. You’ll then learn about picking the right foundation model to suit your use case.