Applying Risk & Chance to Life & Business

Decision Making Under Uncertainty

Learn the basic concepts and tools to help you make better decisions under uncertainty, take calculated risks, and reduce the stress and regrets that often come with decision making. This video is the 1st of a total of 40 short videos. Click here to watch the rest of the videos.

Use probabilistic thinking to increase your chance of success and manage risks

Improve your real life decision making and reduce stress and regrets

Every day, we have to make decisions but we are often unsure of what to do because of the risks and uncertainties involved. Many of us often regret decisions both big and small, but there are actually many ways we can improve our decision-making and risk management, and reduce the stress and regrets about decisions.

Content and Overview

In this course, our goal is to better understand randomness and uncertainty and learn tools to help us make more educated risks. We'll talk about the different biases we all experience in our intuitive thinking, and then learn how to re-train our brains to approach everyday problems differently. Using probability theory and a bit of math, we'll discuss how to make decisions rationally and efficiently. But don't worry—no math background other than being able to add, subtract, divide, and multiply is required! We'll learn how to make better financial decisions, take smarter risks, and improve nearly every aspect of our lives. Each video is short and concise but filled with interesting and helpful material. Each one is animated, to ensure we grasp the concepts completely, and they all contain engaging, relatable real-life examples. Using these tools, anyone can learn to improve their decision-making, which leads to ultimately minimizing the number of regrets they have. If you'd like to live a more worry-free life with fewer regrets, this course is for you.


Special thanks to Linnea Duley for her great help in preparing the content as well as excellent job in creating the animations.

Brief Introduction to Machine Learning (No Coding)

In a series of few short videos, we will go over a general, non-technical introduction to Machine Learning (ML). We will define and explain a few fundamental concepts in ML, including overfitting, cross-validation, VC-dimension, regularization and others. This module is designed to help a general audience, including newcomers. My hope is that this lesson aids in understanding what applications are best suited for ML, provides intuition behind ML algorithms and conveys the importance of ML in today’s world. This video is the 1st of a total of 7 short videos. Click here to watch the rest of the videos.