Machine Learning and AI Foundations: Causal Inference and Modeling
With Keith McCormick
Liked by 243 users
Duration: 2h 51m
Skill level: Advanced
Released: 7/22/2022
Course details
This course with instructor Keith McCormick provides an introduction to some advanced techniques in causal inference and causal modeling. It builds upon a foundation in Keith’s course, Machine Learning and AI Foundations: Prediction, Causality, and Statistical Inference. Keith focuses the course on three major topics: The power of experiments (and the reality that they aren't always available as an option); the Bayesian statistic philosophy and approach and when it's a good choice; and an introduction to causal modeling with techniques like structural equation modeling and Bayesian networks. Join Keith in this course to learn about these advanced techniques and what makes them both powerful and interesting.
Skills you’ll gain
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Meet the instructor
Learner reviews
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John McDove, BSc.
John McDove, BSc.
Computer Network Manager | Cybersecurity Specialist | IT Systems Expert | Remote-Ready | ALX-certified | Data Scientist | Full-stack Developer
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Khaled M. Ali Aklan Albanna
Khaled M. Ali Aklan Albanna
IT Advisor | AI (Expert Systems & Data Science) | Banking and ERP Systems
Contents
What’s included
- Practice while you learn 1 exercise file
- Test your knowledge 5 quizzes
- Learn on the go Access on tablet and phone
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