Brochure
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- Course Overview
- Uplift modeling I: optimize for influence and persuade by the numbers
- Uplift modeling II: modeling over treatment and control groups
- Uplift modeling III: how it works – for banks and for Obama
- Uplift modeling IV: improving churn modeling, plus other applications
- Accuracy fallacy: orchestrating the media's bogus coverage of ML
- More accuracy fallacies: predicting psychosis, criminality, & bestsellers
- P-hacking: a treacherous pitfall
- P-hacking: your predictive insights may be bogus
- P-hacking: how to ensure sound discoveries
- Ensemble models and the Netflix Prize
- Supercharging prediction: ensembles & the generalization paradox
- DEMO - Training an ensemble model (optional)
- Course conclusions
- Home
- SAS Institute
- Courses
- Four Rare Machine Learning Skills All Data Scientists Need
Four Rare Machine Learning Skills All Data Scientists Need
Quick Facts
| particular | details | ||||
|---|---|---|---|---|---|
|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Learning efforts
1 Hours Per Week
|
Course and certificate fees
Type of course
Free
certificate availability
Yes
certificate providing authority
Coursera
certificate fees
₹2,436
The syllabus
Module 1: Four Rare Machine Learning Skills All Data Scientists Need
Videos
Readings
- The Machine Learning Glossary (optional)
- Complementary readings on uplift modeling (optional)
- Complementary reading related to the accuracy fallacy (optional)
- Complementary materials on p-hacking (optional)
- The generalization paradox of ensembles (optional)
- Further learning options
Practice Exercises
- Uplift modeling I: optimize for influence and persuade by the numbers
- Uplift modeling II: modeling over treatment and control groups
- Uplift modeling III: how it works – for banks and for Obama
- Uplift modeling IV: improving churn modeling, plus other applications
- Accuracy fallacy: orchestrating the media's bogus coverage of ML
- More accuracy fallacies: predicting psychosis, criminality, & bestsellers
- P-hacking: a treacherous pitfall
- P-hacking: your predictive insights may be bogus
- P-hacking: how to ensure sound discoveries
- Ensemble models and the Netflix Prize
- Supercharging prediction: ensembles & the generalization paradox
- Graded course completion quiz
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