Non-technical but informative introduction to the intuition, concepts, aims, and properties of data analytics and machine learning for a data-driven analysis of business processes (like customer behavior, production, turnover…)
Data visualization and descriptive statistics (e.g. the average or variability of prices)
Regression: analyzing associations between business factors (like marketing and sales)
Intuition of machine learning for optimally forecasting future business outcomes (e.g.sales), based on information in past data (e.g. price, quality, competition)
Important concepts of machine learning: alternative algorithms (e.g. decision trees, random forests, lasso, boosting…), performance assessment, and tuning of algorithms
Business cases and practical examples with real data using the no-code software “BigML” – no programming required!
