Flexible learning
Online postgraduate courses
Causal Machine Learning
This course is an introduction to the principles and practices of causal
machine learning. It covers the basics of causal inference, including the identification and estimation of causal effects, as well as the applications of causal machine learning in areas such as health, finance, and social sciences. The course also includes an introduction to common methods and algorithms for causal machine learning, such as instrumental variables, synthetic controls, AB-testing and propensity scores.
This module can be taken as part of a PG Certificate, PG Diploma or Full Masters Program.
-203.jpg)
- 10 Credits
- 100 hours of study
- 15 contact hours
- 85 hours for private study
Faculty
Structure
Structure
Causal Machine Learning is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.
The total number of contact hours is 15 hours. This leaves 85 hours for private study.
Lectures
This module consists of 2 - hour lectures per day for 5 days, plus a 1 - hour tutorial per day.
During their private study, students should read the course literature, work on practical exercises, and write a project report for the examination.
The dates of each lecture are confirmed closer to the start of each term. If you have any questions about dates, please contact edu@timberlake.co.uk.
Stata
Python
Module Programme
Introduction
- Simpson’s Paradox
- Directed Acyclic Graphs (DAG)
- Potential Outcomes Causal Model
- AB-testing and RCT Models
Standard approaches
- Regression and Double Orthogonalization
- Propensity Scores
- Doubly Robust Estimator
Machine Learning approaches
- High-dimension and Variable Selection
- Post-Lasso and Post-Double-Lasso
- Double/debiased Machine learning
Heterogeneous Treatment Effects
- Meta-Learners
- Causal Forest
- Generic Machine Learning
Methods
- Instrumental Variables
- Difference-in-Differences
- Synthetic Control
Prerequisites
English Language Requirements
Both Programmes are open to applicants anywhere in the world. We may ask applicants to provide a recognised English language qualification, dependent upon their nationality and where they have studied/worked previously.
The requirement is an IELTS (Academic) Test with an overall score of at least 6.5, and a minimum of 6.0 in each element of the test. We will also consider other English language qualifications. If their score is below our requirements, they may be eligible for one of Lancaster University's pre-sessional English language programmes.
Academic Requirements
Applicants to the Postgraduate Certificate of Achievement, Postgraduate Certificate, Postgraduate Diploma or full MSc in either programme require either an upper second-class degree in economics, econometrics or related subjects.
Learning Outcomes
- Ability to comprehend concepts and principles of causal inference.
- Proficiency in deploying advanced machine learning methods for causal analysis
- Skills to perform rigorous causal analysis using machine learning techniques
- Hands-on experience in deploying advanced ML methods for causal analysis.
- Understand the basics of causal inference and its role in machine learning
- Identify and estimate causal effects using common methods and algorithms
- Apply causal machine learning to real-world problems in areas such as health, finance, andsocial sciences
- Communicate effectively about causal inference and its applications in machine learning.
Frequently Asked Questions
All sessions are conducted live and online at a scheduled time, but are also recorded. Students may attend live and watch the recordings back to recap the material or watch the recordings only if unable to attend live. We always advise students to attend live where possible as this will allow them the best opportunity to engage with the content and ask the lecturer's questions.
All modules are examined through online coursework submissions, you will have the support of your module lecturer/tutor in this poccess.
No, all necessary software is provided to students.
All courses are recorded and available on the LUMS internet platform throughout the current academic year. They can therefore be viewed 24 hours a day.
Timberlake Consultants and Lancaster University Management School (LUMS) Economics department have a longstanding partnership; combining 40+ years of industry expertise with over 50 years of academic excellence. We are delighted to build on this with our micro-credential postgraduate courses.
Flexible learning
Online postgraduate courses
Specialist courses
Best-in-field experts
Tailored learning
Career-oriented education
Subscribe To Our Newsletter
Flexible learning
Online postgraduate courses
Specialist courses
Best-in-field experts
Tailored learning
Career-oriented education