Exploring the roles of AI-Assisted ChatGPT in the field of data science

¹ Vice President, Standard Chartered Global Business Services Sdn Bhd., Kuala Lumpur, Malaysia, latha.nv@gmail.com.
² Associate Professor, PG and Research Department of Computer Science, Sri Meenakshi Government Arts College for Women, Madurai, Tamil Nadu, India, sujamurugan@gmail.com
³ Student – M.Sc. Cyber Security, School of Computer Science, University of Birmingham, Birmingham, United Kingdom, mukulmech99@gmail.com.
⁴ Student – M.S Data Science, School of Engineering and Applied Sciences, University at Buffalo, The state University of New York, United States of America, vslokesh10@gmail.com

Abstract

In this study, we explore the roles of AI-assisted ChatGPT (Generative Pre-trained Transformer) in the field of data science. AI-assisted ChatGPT, a powerful language model, is fine-tuned using domain-specific data for specialised data science tasks, such as sentiment analysis and named entity recognition (NER). The results reveal significant reductions in model size and memory usage with minor trade-offs in inference time, providing valuable resource-efficient deployment. Various data augmentation methods, including back-translation, synonym replacement, and contextual word embeddings, are employed to augment the training dataset. The study's results are subjected to rigorous statistical analysis, including paired t-tests and ANOVA tests, to determine the significance of the findings. The research concludes with insightful suggestions and future scope, including advanced fine-tuning strategies, model optimization techniques, and ethical considerations.