中国科大地空学院“瀚海问天”日地空间物理前沿论坛讲座第34期-Norbert Gyenge

报告人简介：      

         Dr Norbert Gyenge is a Research Computing Training Lead at the University of Sheffield, where he develops and delivers training in programming, data science, high-performance computing, and generative artificial intelligence. His work focuses on making complex computational concepts accessible to diverse academic audiences and supporting the responsible adoption of AI technologies in education and research. He regularly teaches foundational topics in artificial intelligence, including neural networks, and contributes to the development of institutional strategies for digital and AI skills.

摘要：

        Artificial intelligence and neural networks are no longer confined to computer science; they are increasingly relevant across research, education, and professional practice. However, much of the existing educational material assumes programming and mathematical backgrounds that many learners do not possess, creating a skills gap that leads to inefficient and often frustrating learning experiences.

      This talk addresses that gap by introducing neural networks through an accessible, concept-driven framework designed for learners from diverse disciplines. The session aims to demystify how neural networks work, clarify common misconceptions, and provide a foundation for engaging confidently with modern AI technologies regardless of prior technical background.