diff --git a/README.md b/README.md
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@@ -704,6 +704,9 @@ Topics covered include probability theory and Bayesian inference; univariate dis
 	- Basic and advanced techniques for text-based information systems: efficient text indexing; Boolean and vector space retrieval models; evaluation and interface issues; Web search including crawling, link-based algorithms, and Web metadata; text/Web clustering, classification; text mining.
 	- [Lecture notes](http://web.stanford.edu/class/cs276/index.html#syllabus)
 	- [Readings](http://web.stanford.edu/class/cs276/index.html#books)
+- [Practical_RL](https://github.com/yandexdataschool/Practical_RL) **Reinforcement Learning in the Wild** *Yandex SDA* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
+	- A course on reinforcement learning in the wild. Taught on-campus in HSE and Yandex SDA (russian) and maintained to be friendly to online students (both english and russian).
+	- [Syllabus](https://github.com/yandexdataschool/Practical_RL#syllabus)
 
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