Project managers and professionals in engineering and software development need to perform data analytics on a daily basis. This course is an introduction to identifying, analyzing, assessing, and managing data inherent to engineering projects.
It includes: Bayesian statistical principles, concepts, and models; decision science aspects of data systems; measurement theory; subjective aspects of statistics and data appraisal. Examples are drawn from software development, systems integration, and large infrastructure engineering projects. Covers statistical basics, Bayesian data analysis, simulation, predictive analytics.
• Identify salient aspects of data development systems in the project environment
• Interpret project performance data using descriptive analytics
• Analyze project data using Bayesian analytics and predictive analysis
• Relate decision engineering to prescriptive analysis in project management
• Organize data analytics programs for unique projects, programs, and portfolios