Course Summary
This course teaches interventions and calibration techniques for effective decision-making. You will learn how to identify and address biases, and use data-driven methods to make better decisions.Key Learning Points
- Understand biases and how they affect decision-making
- Learn intervention techniques to address biases
- Master calibration techniques to make data-driven decisions
Job Positions & Salaries of people who have taken this course might have
- Data Analyst
- USA: $62,453
- India: ₹499,753
- Spain: €29,900
- Business Analyst
- USA: $70,446
- India: ₹672,898
- Spain: €34,100
- Decision Scientist
- USA: $102,000
- India: ₹1,825,000
- Spain: €50,000
Related Topics for further study
Learning Outcomes
- Identify biases and address them in decision-making
- Apply intervention and calibration techniques for better decision-making
- Make data-driven decisions with confidence
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of statistics
- Familiarity with decision-making processes
Course Difficulty Level
IntermediateCourse Format
- Online self-paced course
- Video lectures
- Quizzes and assignments
Similar Courses
- Data-driven Decision-making
- Behavioral Economics and Decision-making
- Applied Data Science: Interventions and Applications
Related Education Paths
Notable People in This Field
- Psychologist and Nobel Laureate
- Legal Scholar and Behavioral Economist
Related Books
Description
This course covers approaches for modelling treatment of infectious disease, as well as for modelling vaccination. Building on the SIR model, you will learn how to incorporate additional compartments to represent the effects of interventions, such the effect of vaccination in reducing susceptibility. You will learn about ‘leaky’ vaccines and how to model them, as well as different types of vaccine and treatment effects. It is important to consider basic relationships between models and data, so, using the basic SIR model you have developed in course 1, you will calibrate this model to epidemic data. Performing such a calibration by hand will help you gain an understanding of how model parameters can be adjusted in order to capture real-world data. Lastly in this course, you will learn about two simple approaches to computer-based model calibration - the least-squares approach and the maximum-likelihood approach; you will perform model calibrations under each of these approaches in R.
Knowledge
- Identify the relationship between models and real-world epidemiological data
- Incorporate treatment or vaccination into an SIR model, accounting for imperfect efficacy, and for different mechanisms of action
- Perform simple calibrations of an SIR model against time-series data, selecting parameters to maximise the fit of the model to the data
- Recognise two simple approaches to computer-based model calibration and perform model calibrations under each of these approaches in R.
Outline
- Modelling Interventions
- Welcome to the Course
- An Insider's View of IDM
- Modelling Curative Treatment
- Modelling Vaccination: Leaky Vaccines
- Modelling Vaccination: Additional Vaccine Effects
- Welcome to Infectious Disease Modelling
- About the Infectious Disease Modelling Team
- Glossary
- Modelling Infectious Disease Dynamics
- Modelling Vaccination: First Steps
- Confronting Models with Data - Part A
- Models and Data: A Brief Detour into the Solar System
- Relationships Between Models and Data
- Modelling with Insufficient Data
- Modelling with Sufficient Data
- Confronting Models with Data - Part B
- Computer-based Calibration: The Overall Approach
- Introduction to Least-Squares Calibration
- Recap: Least-squares Estimation
- Confronting models with data – Part C
- The Concept of Likelihood
- Constructing a Likelihood Function
- To Log or not to Log?
- Overview of Model Calibration
- Modelling Project
- Which is the Correct Code Block?
- Modelling outputs
Summary of User Reviews
Read reviews and ratings for Interventions and Calibration, a course from University of Michigan. Explore the course description, learn about upcoming sessions and enroll online.Pros from User Reviews
- The course covers a wide range of topics related to interventions and calibration.
- The instructors are knowledgeable and provide clear explanations.
- The assignments and quizzes are challenging but doable.
- The course is well-structured and easy to follow.
- The course materials are easily accessible and well-designed.
Cons from User Reviews
- Some users found the course to be too theoretical and not practical enough.
- The pace of the course can be slow at times.
- Some users felt that the course could benefit from more real-world examples.
- The course may be too basic for advanced learners.
- The discussion forums can be overwhelming and hard to keep up with.
Nimalan Arinaminpathy
4.6 Raiting
Interventions and Calibration
- 4.6
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This course covers approaches for modelling treatment of infectious disease, as well as for modelling vaccination. Modelling Interventions Welcome to the Course...
