Introduction to Spreadsheets and Models

The first module provides an overview of the historical context and functions of spreadsheets, equipping learners with the fundamental skills to navigate Excel or Sheets. Participants will delve into crafting formulas, using functions, conditional expressions, and common errors in spreadsheets. The module also covers the differences between Sheets and Excel, preparing participants to build models and decision trees in subsequent courses.

Module two focuses on transitioning from spreadsheets to models, emphasizing the use of assumptions and decision variables in spreadsheet models. Participants will learn to structure a spreadsheet to model variables, objectives, and objective functions, and construct simple cashflow models. The module also explores what-if analysis, sensitivity analysis, and the limits of simple, deterministic models, empowering learners to make informed decisions based on data modeling.

Addressing uncertainty and probability in models, the third module delves into random variables, probability distributions, and changes in discrete and continuous time. Participants will explore power, exponential, and log functions, as well as probability trees, decision trees, correlation, and regression. The module also provides additional reading on exponential and other functions, enhancing participants' understanding of uncertainty and probability in data analysis and modeling.

The final module focuses on simulation and optimization techniques, encompassing Monte Carlo simulations and linear programming. Participants will gain insights into the next steps and differences between Excel and Sheets, equipping them with the skills to apply simulation and optimization to make informed decisions based on data analysis. The module also offers links and other resources for further study, enabling learners to deepen their expertise in simulation, scenarios, and optimization techniques.