Wojciech 'Victor' Fulmyk is an accomplished instructor at IBM, specializing in artificial intelligence and data science education. He teaches several online courses on Coursera, including Generative AI Advance Fine-Tuning for LLMs and Deep Learning with Keras and TensorFlow, where he imparts his extensive knowledge of machine learning and neural networks to a global audience. With a strong academic background as a Ph.D. candidate in Economics at the University of Calgary, Victor combines theoretical insights with practical applications in his teaching. His expertise is further demonstrated through his competitive success on platforms like Kaggle, where he has achieved top rankings in challenging data science competitions. Victor's commitment to advancing the field of AI education is evident in his innovative course offerings that prepare learners for the rapidly evolving tech landscape, making him a valuable asset to both IBM and the broader educational community.

Kang Wang is a dedicated Data Scientist Intern at IBM and a PhD candidate at the University of Waterloo, where he focuses on the intersection of theoretical research and practical applications in data science. His work involves extensive data analysis and model development in machine learning and artificial intelligence, aiming to enhance understanding and implementation of these technologies in real-world scenarios. Kang has also contributed to the academic community by teaching courses such as Generative AI Language Modeling with Transformers and Fundamentals of AI Agents Using RAG and LangChain, helping students grasp complex concepts in AI. His commitment to advancing the field is evident through his innovative projects and collaborative efforts, making him a valuable asset in the realm of data science and machine learning.