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 |      21       | ⚡️ World Power Usage ⚡️ Time Series Forecasting with ARIMA ⚡️ |        [Time Series](7-TimeSeries/README.md)        | Time Series Forecasting with ARIMA                                                                                              |       [lesson](7-TimeSeries/2-ARIMA/README.md)        |  Francesca  |
 |      22       |           Introduction to Reinforcement Learning           | [Reinforcement Learning](8-Reinforcement/README.md) | tbd                                                                                                                             |                      [lesson]()                       |   Dmitry    |
 |      23       |                Help Peter avoid the Wolf! 🐺                | [Reinforcement Learning](8-Reinforcement/README.md) | tbd                                                                                                                             |                      [lesson]()                       |   Dmitry    |
-|      24       |          Real-World ML Scenarios and Applications          |                   ML in the Wild                    | Interesting and Revealing real-world applications of classical ML                                                               |    [lesson](9-Real-World/1-Applications/README.md)    |    Team     |
+|      24       |          Real-World ML Scenarios and Applications          |                   [ML in the Wild](9-Real-World/README.md)                    | Interesting and Revealing real-world applications of classical ML                                                               |    [lesson](9-Real-World/1-Applications/README.md)    |    Team     |
 ## Offline access

 You can run this documentation offline by using [Docsify](https://docsify.js.org/#/). Fork this repo, [install Docsify](https://docsify.js.org/#/quickstart) on your local machine, and then in the root folder of this repo, type `docsify serve`. The website will be served on port 3000 on your localhost: `localhost:3000`.