Loading...
Dr. Poonam Saini is an Assistant Professor in the Faculty of Computing and Informatics at Sir Padampat Singhania University, Udaipur, Rajasthan, India. Her research areas include big data analytics, machine learning, AI-driven recommendation systems, and skill gap analysis.
The chapter examines machine learning methodologies, including classification, clustering, natural language processing, and recommendation systems, for aligning individual competencies with industry norms. It emphasises the significance of big data frameworks in processing varied and substantial datasets to produce real-time insights. A comprehensive framework for identifying skill gaps and recommending training is proposed, highlighting automation, scalability, and personalisation. Additionally, difficulties of data privacy, bias, model interpretability, and organisational adoption are thoroughly examined. Emerging developments, including AI-driven career pathing, adaptive learning systems, and predictive workforce analytics, are also examined. Organisations and educational institutions may utilise AI and big data to augment talent development, enhance productivity, and synchronise staff competencies with changing market demands.