The Applied Data Science and Analysis aims to serve as a premier platform for researchers, practitioners, and professionals involved in the application of data science across various domains. The journal welcomes contributions that highlight the practical implementation and real-world impact of data science techniques, methodologies, and tools.

By providing a platform for applied data science research, the Applied Data Science and Analysis journal aims to bridge the gap between academia and industry, foster knowledge exchange, and contribute to the advancement of data-driven decision-making in various sectors.

The Applied Data Science and Analysis journal include a wide range of subjects related to data science and its practical applications. The journal focuses on publishing high-quality research and advancements in the field. The following are the major topics of interest:

 

• Data Mining and Knowledge Discovery
• Machine Learning and Artificial Intelligence
• Big Data Analytics
• Predictive Analytics and Forecasting
• Natural Language Processing
• Computer Vision and Image Analysis
• Social Network Analysis
• Optimization and Operations Research
• Fuzzy Decision Making
• Data Visualization and Visual Analytics
• Ethical and Privacy Issues in Data Science
• Real-world Applications of Data Science
• Data Engineering and Data Infrastructure