ISCSITR - International Journal of Data Science (ISCSITR-IJDS) is a leading open-access, peer-reviewed journal sponsored by the International Society for Computer Science and Information Technology Research (ISCSITR). This journal is dedicated to the field of data science, offering a comprehensive forum for researchers, data scientists, and industry professionals to present their latest research findings, innovative methodologies, and technological advancements.
The ISCSITR-IJDS covers a wide array of topics within data science, including but not limited to big data analytics, statistical methods, data mining, machine learning, predictive modeling, data visualization, data infrastructure, data privacy and security, and the application of data science techniques in various industries like healthcare, business, finance, and telecommunications.
The journal aims to foster a deeper understanding of the vast potentials and challenges in the field of data science, promoting the development of more efficient, effective, and innovative data-driven methodologies and technologies. By maintaining an open-access model, the ISCSITR-IJDS ensures that all content is freely available, facilitating greater dissemination of information and collaboration among data science professionals worldwide. This makes it an invaluable resource for anyone involved in or interested in the latest developments in the field of data science.
