
Course overview, instructor presentation.
The difference between tacit and explicit and qualitative and quantitative information, and implications for decision-making.
The role of logic in qualitative decision-making and introduction of the use of visual diagrams.
What are Large Language Models. How do they work, what are their strengths and weaknesses. Introduction to a case study which will be used in the subsequent lecture.
Using Chat GPT to look for logical flaws in a cause-effect diagram. How to build a combined prompt to identify multiple issues in one go.
The ability to effectively communicate with Large Language Models is fast becoming the single most important skill to have, and there is little doubt it is already starting to distinguish between winners and losers in the workplace.
The danger of losing out to AI is real. But if we use it correctly, it can help us become better at thinking and make better decisions.
Decision-making and analysis in complex situations calls for rigorous cause-effect analysis. Until now, the drawback of such analysis has been the time and effort it calls for. With the new natural language AI models, this is now fundamentally changing.
In this course, I explain step-by-step how to prompt AI for valid responses on cause-effect relationships. When you finish, you will be able to take advantage of AI to transform your thinking and take your decision-making and problem-solving skills to a new level.
In the course, you will also learn the basics of the Logical Thinking Process framework, which is the most powerful methodology available for sound cause-effect analysis and decision-making. It is based on the groundbreaking work of management pioneer Dr. Eliyahu M. Goldratt, author of the best selling business novel The Goal.
Note: This is NOT a generic prompt engineering course. It is highly specialized and intended for those who understand the threats and opportunities brought by the new Large Language Models, and who are ready to take advantage of this new technology to transform their own thinking.