Each module is designed to help you craft the narrative for your company’s data literacy by improving your own data fluency and gaining an understanding of the business value quality data and expert analytics can create for your business.
Dive into the fundamentals by comparing the various types of data analysis, examining variables, and analyzing the impact of sample size and sample bias.
Perhaps the single most essential tool in statistical modeling, regression is central to data literacy. Learn what regression does, how it fits into prediction, and what questions to ask data analysts (and yourself).
Do you know your dashboards? Understand the applications of data analytics dashboards and the use of conditional averages, distributions, regression to the mean, and hypothesis testing to devise Key Performance Indicators (KPIs)
Scientific Thinking in Business: Prescriptive Analysis
How do you mold raw data into a business strategy? Examine cause and effect in data analysis, design an experiment, analyze causal inference without experiments, and be prepared to prescribe a response to the likely results.
Introduction to Prediction
If futurecasting appeals to your strategic side, it’s critical to understand predictive analysis, the construction of a prediction model, the application of machine learning and AI to prediction, and the strategic implications of prediction.
Building a Data-Driven Organization
Widen your view of data literacy to your whole workforce. Develop an organizational model for a question-driven approach to data analysis, understand privacy concerns, and formulate a strategy to build an evidence- and learning-based corporate culture.