A data science course utilizing genAI

This innovative practice full paper describes an indepth analysis of the pedagogical implications of incorporating generative artificial intelligence (genAI) tools, specifically Chat-GPT, into a data science course for postgraduate masters computing students. This research is grounded in the implementation of ChatGPT in a data analysis course, aiming to evaluate its effectiveness in fostering students' analytical and decision-making capabilities. The study employs a qualitative methodology to assess the educational outcomes of integrating ChatGPT, focusing on its impact on student engagement, learning efficiency, and the development of critical thinking skills in the context of data science. Through a combination of interviews, and analysis of students' project outcomes, we gather insights into the challenges and opportunities presented using genAI in the data science course. A notable innovation of our approach is the introduction of a dual-report assessment method, which not only evaluates the students' project results but also their proficiency in prompt engineering - a crucial skill for effective interaction with genAI tools. Our findings suggest that while students demonstrate enhanced data analysis skills, they also face difficulties in accurately framing queries to yield useful results from genAI, highlighting an essential area for further curriculum development. Further-more, the work delves into the pedagogical strategies that can optimize the benefits of genAI tools in education. It emphasizes the importance of a structured framework that guides students in the ethical use of genAI, encourages critical reflection on AI-generated content, and fosters a deeper understanding of the underlying algorithms and their implications for data science. The implications of this research extend beyond the classroom, offering valuable insights for instructors, curriculum developers, and policymakers on integrating AI technologies into educational practices. By providing a comprehensive overview of the benefits and challenges associated with the use of ChatGPT in data science education, this paper contributes to the ongoing dialogue on preparing students for a future where genAI might a significant role. In conclusion, this work highlights the potential of genAI to revolutionize data science education by enhancing analytical skills and decision-making capabilities. Continued exploration of effective strategies for integrating AI tools into learning environments, such as data science, is required to ensure that students are equipped with the knowledge and skills necessary to navigate the complexities of genAI for future employment.