Citation

Khan, M. Reyasudin Basir and Islam, Gazi Md. Nurul and Ng, Poh Kiat and Zainuddin, Ahmad Anwar and Lean, Chong Peng and Al-Fattah, Jabbar and Basri, Atikah Balqis and Kamarudin, Saidatul Izyanie (2024) Exploring salary trends in data science, artificial intelligence, and machine learning: A comprehensive analysis. In: THE 6TH ISM INTERNATIONAL STATISTICAL CONFERENCE (ISM-VI) 2023, 19–20 September 2023, Shah Alam, Malaysia.

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Abstract

The rapid advancement of Data Science, Artificial Intelligence, and Machine Learning has created a dynamic job market. In line with other professions, salaries are provided as a means of compensating professionals for their work. However, it is evident from previous research that salary levels vary across different job fields, as each field contributes uniquely to its respective domain. The magnitude of this contribution directly influences the salary structure within a field. To shed light on this phenomenon, this data analysis project aims to examine the salaries dataset. The project’s objective is to identify the factors that influence salary levels in these fields through comprehensive analysis. By exploring these trends, we can gain insights into the continued value of these fields in the coming years.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	01 Oct 2024 01:13
Last Modified:	01 Oct 2024 01:13
URII:	http://shdl.mmu.edu.my/id/eprint/13002

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