AI-Powered Data Science: A Review of Current Developments and Emerging Opportunities

Abstract

Data Science with AI combines the capabilities of AI and traditional data science, offering improved data analysis, prediction, and decision-making functions. This review delves into key concepts like machine learning, deep learning, and big data, as well as cutting-edge advancements such as AutoML, generative AI, explainable AI, and real-time analytics. It showcases real-world examples from industries such as healthcare, finance, manufacturing, retail, transportation and education, pointing to its broad industry applications. The study also covers emerging areas such as human-AI collaboration, predictive analytics and democratization of data science. Issues of privacy, bias, scalability and transparency are explored. Lastly, ethical AI, federated learning and autonomous systems development are highlighted as future directions.