Unlock the full potential of data-informed decision-making in this hands-on track. Begin with the fundamentals of decision science—problem framing, modeling, and ethical considerations. Then, master tools like decision trees, expected value analysis, and scenario modeling to make strategic, data-backed choices. Round out your skills with techniques to recognize, measure, and mitigate bias in data collection, analysis, and decision logic. By working through real-world case studies and interactive exercises, you’ll gain the confidence and credibility to make fair, transparent, and effective decisions across a wide range of industries.
Overview
Syllabus
- Demystifying Decision Science
- Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.
- Decoding Decision Modeling
- Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
- Conquering Data Bias
- Unlock your data's potential by learning to detect and mitigate bias for precise analysis and reliable models.
Taught by
Konstantinos Kattidis, Tiago Brasil, Howard Friedman, and Akshay Swaminathan
