Various reports relating to data science and business strategy. The reports focus on making data-driven decisions that propel organizations forward. The analysis for the reports are derived from database systems and analytics software built upon open-source systems such as R, Python, and TensorFlow. The recommendation is based on trustworthy predictions using traditional statistics and machine learning methods.
There are four areas of the reports: Analytics and Modeling, Artificial Intelligence, Data Engineering, or Analytics Management. Each report digs deeper in various data science concepts including financial and risk analytics, artificial intelligence and deep learning, analytics systems analysis, and information retrieval and real-time analytics.
The reports may also discuss leadership theory and associated behaviors that enable organizations to excel in their analytics units and to apply these behaviors to personal and professional success. The analytics-specific project management reports will showcase where the design from an analytics project plan using an agile approach incorporating CRISP-DM methodology, and execute that plan in a simulated business setting. Leadership challenges unique to analytics departments in various company sizes will be addressed through the use of case studies and theory-based assignments.