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Neuroeconomics Course

Neuroeconomics Course
4 to 360 hours of flexible workload
certificate valid in your country

What Will I Learn?

This Neuroeconomics Course equips you with a practical toolkit to grasp how the brain influences saving and retirement decisions. Delve into core neural systems for valuation and self-control, essential behavioural mechanisms such as present bias and loss aversion, and practical techniques including fMRI, EEG, and eye-tracking. Develop rigorous, ethical studies and apply neural insights to create effective, testable interventions and policies for retirement.

Elevify Advantages

Develop Skills

  • Diagnose retirement biases: spot present bias, loss aversion, and inertia.
  • Interpret brain signals: analyse fMRI, EEG, and physiological responses in economic decisions.
  • Design efficient neuroeconomic studies: plan tasks, sampling, and incentive frameworks.
  • Connect neural data to models: adjust discounting, risk, and self-control parameters.
  • Transform neural insights into policy: develop smarter defaults, nudges, and commitment devices.

Suggested Summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

Your classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons get straight to the point and how I can switch chapters and skip content I don't need.
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Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!
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Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the supplementary videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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