Teacher
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Algherini Samuel
(syllabus)
The lab aims to deliver students solid theoretical foundations of AI and a well-established ability to interact with Large Language Models through the best prompt engineering techniques. The lab consists of a more theoretical first phase where we will cover the basics of AI and understand how a neural network works. We will also see the ethical issues related to these models, such as the creation of biased models, the data protection problem and the explainability problem, i.e., The ability to understand why a result was provided. Second, once this knowledge is acquired, we will pay attention to how LLMs work. We will see the architecture of these models and we will move on to study and rehearse together the most current prompt engineering techniques and different possible methods to relate to these models and get the best answers. No prior knowledge of code is necessary.
(reference books)
Resources provided by the professor during the course
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