2025-04-23 –, Europium2
The rapid evolution of AI technologies, particularly since the emergence of Large Language Models, has transformed the data science landscape from a field of steady progress to one of constant breakthroughs. This acceleration creates unique challenges for practitioners, from managing FOMO to battling imposter syndrome. Drawing from personal experience transitioning from mathematical modeling to modern AI development, this talk explores practical strategies for staying current while maintaining sanity. We'll discuss building effective learning structures, creating collaborative knowledge-sharing environments, and finding the right balance between innovation and implementation. Attendees will leave with actionable insights on navigating technological change while fostering sustainable growth in their teams and careers.
The landscape of data science and AI is evolving at an unprecedented rate. What started as a relatively stable field of mathematical modeling and time-series analysis has transformed into a whirlwind of weekly breakthroughs, especially since the emergence of Large Language Models. How do we stay current without succumbing to FOMO or imposter syndrome?
In this talk, I'll share my personal journey from traditional mathematical modeling to modern AI development, exploring how the field's pace has shifted dramatically. Drawing from real-world experiences as a consultant and team lead, I'll discuss practical strategies for maintaining technical excellence while managing the psychological challenges of rapid technological change. We'll examine how to build effective learning structures within teams, the importance of creating safe spaces for knowledge sharing, and why sometimes it's okay to not be at the cutting edge of every new development.
Through concrete examples and lessons learned, I'll offer insights on balancing client expectations, team growth, and personal development in an era where the technological landscape shifts weekly. Whether you're a seasoned data scientist or just entering the field, this talk will provide practical frameworks for navigating the exciting yet overwhelming world of modern AI development.
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Expected audience expertise: Python:None
Hi! I am Carsten. I have been working in the data and analytics environment for seven years. As a data scientist, I am excited by the challenge of translating the business into optimizable algorithms and creating real impact. As a self-taught programmer, I am just as absorbed in the technical challenges, preferably in the cloud.