diff --git a/docs/configs/env_vars.md b/docs/configs/env_vars.md
index 11f1270d..477f4c46 100644
--- a/docs/configs/env_vars.md
+++ b/docs/configs/env_vars.md
@@ -16,7 +16,7 @@ but can be overridden by command-line arguments.
 |Name| Description                                                                    |
 |---|--------------------------------------------------------------------------------|
 |**CLEARML_LOG_ENVIRONMENT** | List of Environment variable names. These environment variables will be logged in the ClearML task’s configuration hyperparameters `Environment` section. When executed by a ClearML agent, these values will be set in the task’s execution environment. |
-|**CLEARML_TASK_NO_REUSE** | Boolean. <br/> When set to `true`, a new task is created for every execution (see Task [reuse](../clearml_sdk/task_sdk#task_reuse).                                                              |
+|**CLEARML_TASK_NO_REUSE** | Boolean. <br/> When set to `true`, a new task is created for every execution (see Task [reuse](../clearml_sdk/task_sdk#task-reuse).                                                              |
 |**CLEARML_CACHE_DIR** | Set the path for the ClearML cache directory, where ClearML stores all downloaded content.   |
 |**CLEARML_DOCKER_IMAGE** | Sets the default docker image to use when running an agent in [Docker mode](../clearml_agent.md#docker-mode).  |
 |**CLEARML_LOG_LEVEL** | Sets the ClearML package's log verbosity. Log levels adhere to [Python log levels](https://docs.python.org/3/library/logging.config.html#configuration-file-format): CRITICAL, ERROR, WARNING, INFO, DEBUG, NOTSET |
diff --git a/docs/getting_started/video_tutorials/hands-on_mlops_tutorials/how_clearml_is_used_by_a_data_scientist.md b/docs/getting_started/video_tutorials/hands-on_mlops_tutorials/how_clearml_is_used_by_a_data_scientist.md
index c07aaa08..220ff7a2 100644
--- a/docs/getting_started/video_tutorials/hands-on_mlops_tutorials/how_clearml_is_used_by_a_data_scientist.md
+++ b/docs/getting_started/video_tutorials/hands-on_mlops_tutorials/how_clearml_is_used_by_a_data_scientist.md
@@ -70,7 +70,7 @@ it to you later in the UI, we have a nice and clear overview of all of the diffe
 
 I'll add some dataset statistics that's also something you can do and ClearML is just add some, for example, class 
 distribution or other kind of plots that could be interesting, and then I'm actually building the ClearML dataset here. 
-Also, an an extra thing that is really, really useful if you use ClearML datasets is you can actually share it as well. 
+Also, an extra thing that is really, really useful if you use ClearML datasets is you can actually share it as well. 
 So not only with colleagues and friends, for example. You can share the data with them, and they can add to the data, and 
 always you will always have the latest version, you will always know what happened before that.