Big Data Analytics for Cybersecurity

Catalog description

Data devel - opment and management, machine learning and natural language pro- cessing, statistical analysis, data visualization, and inference are among the major knowledge areas in data science that are covered in this course. Using well-known modules like sklearn, Pandas, matplotlib, and numPy, students will use Python to analyze regression models (Linear, Multilinear, and Polynomial) and classification models (kNN, Logistic). In both employment and research settings, students will learn about the storage, processing, analysis, visualization, and use of big data. The course covers modern Big Data technologies, platforms, and algorithms in practical applications. To succeed in this course, students must pos - sess a minimal level of programming knowledge, ideally in Python.