diff --git a/docs/fundamentals/pipelines.md b/docs/fundamentals/pipelines.md
index df7976f6..3a14852e 100644
--- a/docs/fundamentals/pipelines.md
+++ b/docs/fundamentals/pipelines.md
@@ -25,7 +25,7 @@ create customized, step-specific callbacks.
 ![Pipeline chart](../img/fundamentals_pipeline.png)
 
 
-## Simple DAG Pipelines
+## Simple DAG pipelines
 
 For a simple, DAG based logic, use the off-the-shelf [`PipelineController`](../references/sdk/automation_controller_pipelinecontroller.md) class to define the DAG (see an example 
 [here](../guides/pipeline/pipeline_controller)). Once the `PipelineController` object is populated and configured, 
@@ -56,7 +56,7 @@ It could also be useful to run a pipeline that runs tasks concurrently, training
 values simultaneously. See the [Tabular training pipeline](../guides/frameworks/pytorch/notebooks/table/tabular_training_pipeline.md) 
 example of a pipeline with concurrent steps. 
 
-## Custom Pipelines
+## Custom pipelines
 
 In cases where a DAG is insufficient (for example, when needing to launch one pipeline, then, if performance is inadequate, 
 rerun pipeline again), users can apply custom logic, using generic methods to enqueue tasks, implemented in python code.
diff --git a/docs/fundamentals/task.md b/docs/fundamentals/task.md
index 48a19136..2eee4802 100644
--- a/docs/fundamentals/task.md
+++ b/docs/fundamentals/task.md
@@ -268,7 +268,7 @@ cloned = Task.clone(
 )
 ```
 
-A cloned Task starts in [draft](#task-states-and-state-transitions) mode, so its Task configurations can be edited (see 
+A cloned Task starts in [draft](#task-states) mode, so its Task configurations can be edited (see 
 [Task.set_parameters](../references/sdk/task.md#set_parameters)).
 Once a Task is modified, launch it by pushing it into an execution queue, then a [ClearML Agent](../clearml_agent) will pull 
 it from the queue and execute the Task.
diff --git a/docs/hyperdatasets/annotations.md b/docs/hyperdatasets/annotations.md
index ce609233..21e96b65 100644
--- a/docs/hyperdatasets/annotations.md
+++ b/docs/hyperdatasets/annotations.md
@@ -8,7 +8,7 @@ two types of annotations: **Frame objects** and **Frame labels**.
 Annotation Tasks can be used to efficiently organize the annotation of frames in Dataset versions (see 
 [Annotations Task Page](webapp/webapp_annotator.md)).  
 
-For information about how to view, create, and manage annotations using the WebApp, see [Annotating Images and Videos](#annotating-images-and-video).
+For information about how to view, create, and manage annotations using the WebApp, see [Annotating Images and Videos](webapp/webapp_annotator.md#annotating-images-and-video).
 
 ## Frame objects
 
@@ -27,7 +27,7 @@ Frame labels are applied to an entire frame, not a region in a frame.
 
 ### Adding a frame object
 
-To add a frame object annotation to a SingleFrame, use the [`SingleFrame.add_annotation`](google.com) method.  
+To add a frame object annotation to a SingleFrame, use the `SingleFrame.add_annotation` method.  
 
 ```python
 # a bounding box labeled "test" at x=10,y=10 with width of 30px and height of 20px
@@ -41,14 +41,14 @@ When adding an annotation there are a few options for entering the annotation's
 * `poly2d_xy` - A list of floating points (x,y) to create for single polygon, or a list of Floating points lists for a 
   complex polygon
 * `ellipse2d_xyrrt` - A List consisting of cx, cy, rx, ry, and theta for an ellipse 
-* And more! See [`SingleFrame.add_annotation`](google.com) for further options. 
+* And more! See `SingleFrame.add_annotation` for further options. 
 
 ### Adding a Frame label
 
 Adding a frame label is similar to creating a frame objects, except that coordinates don't need to be specified, since 
 the whole frame is being referenced. 
 
-Use the [`SingleFrame.add_annotation`](google.com) method, but use only the `labels` parameter. 
+Use the `SingleFrame.add_annotation` method, but use only the `labels` parameter. 
 
 ```python
 # labels for the whole frame        
diff --git a/docs/hyperdatasets/custom_metadata.md b/docs/hyperdatasets/custom_metadata.md
index 38b2b42c..6b4e420c 100644
--- a/docs/hyperdatasets/custom_metadata.md
+++ b/docs/hyperdatasets/custom_metadata.md
@@ -30,7 +30,7 @@ frame.metadata['dangerous'] = 'no'
 
 ### Adding ROI metadata
 
-Metadata can be added to individual ROIs when adding an annotation to a `frame`, using the [`add_annotation`](google.com)
+Metadata can be added to individual ROIs when adding an annotation to a `frame`, using the `add_annotation`
 method. 
 
 ```python
diff --git a/docs/hyperdatasets/dataset.md b/docs/hyperdatasets/dataset.md
index ecb2f2ff..5e37938f 100644
--- a/docs/hyperdatasets/dataset.md
+++ b/docs/hyperdatasets/dataset.md
@@ -37,7 +37,7 @@ with an "Example" banner in the WebApp (UI).
 
 ### Creating Datasets
 
-Use the [Dataset.create](google.com) method to create a Dataset. It will contain an empty version named `Current`.
+Use the `Dataset.create` method to create a Dataset. It will contain an empty version named `Current`.
 
 ```python
 from allegroai import Dataset
@@ -45,7 +45,7 @@ from allegroai import Dataset
 myDataset = Dataset.create(dataset_name='myDataset')
 ```
 
-Or, use the [DatasetVersion.create_new_dataset](google.com) method.
+Or, use the `DatasetVersion.create_new_dataset` method.
 
 ```python
 from allegroai import DatasetVersion
@@ -132,7 +132,7 @@ a Dataset version that yields a parent with two children, or when publishing the
 
 ## Versioning Usage
 
-Manage Dataset versioning using the [DatasetVersion](google.com) class in the ClearML Enterprise SDK.
+Manage Dataset versioning using the DatasetVersion class in the ClearML Enterprise SDK.
 
 ### Creating snapshots
 
@@ -140,7 +140,7 @@ If the Dataset contains only one version whose status is *Draft*, snapshots of t
 When creating a snapshot, the current version becomes the snapshot (it keeps the same version ID),
 and the newly created version (with its new version ID) becomes the current version.
 
-To create a snapshot, use the [DatasetVersion.create_snapshot](google.com) method. 
+To create a snapshot, use the `DatasetVersion.create_snapshot` method. 
 
 
 #### Snapshot naming
@@ -205,7 +205,7 @@ myDataset = DatasetVersion.create_snapshot(dataset_name='MyDataset',
 
 Create a new version from any version whose status is *Published*. 
 
-To create a new version, call the [DatasetVersion.create_version](google.com) method, and
+To create a new version, call the `DatasetVersion.create_version` method, and
 provide: 
 * Either the Dataset name or ID
 * The parent version name or ID from which the child inherits frames 
@@ -241,7 +241,7 @@ myDataset = DatasetVersion.create_version(dataset_name='MyDataset',
 
 ### Getting versions
 
-To get a version or versions, use the [DatasetVersion.get_version](google.com) and [DatasetVersion.get_versions](google.com) 
+To get a version or versions, use the `DatasetVersion.get_version` and `DatasetVersion.get_versions` 
 methods, respectively.
 
 **Getting a list of all versions**
@@ -281,7 +281,7 @@ myDatasetversion = DatasetVersion.get_version(dataset_name='MyDataset',
 
 ### Deleting versions
 
-Delete versions which are status *Draft* using the [Dataset.delete_version](google.com) method.
+Delete versions which are status *Draft* using the `Dataset.delete_version` method.
 
 ```python
 from allegroai import Dataset
@@ -293,7 +293,7 @@ myDataset.delete_version(version_name='VersionToDelete')
 
 ### Publishing versions
 
-Publish (make read-only) versions which are status *Draft* using the [Dataset.publish_version](google.com) method. This includes the current version, if the Dataset is in
+Publish (make read-only) versions which are status *Draft* using the `Dataset.publish_version` method. This includes the current version, if the Dataset is in
 the simple version structure.
 
 ```python
diff --git a/docs/hyperdatasets/dataviews.md b/docs/hyperdatasets/dataviews.md
index 302bd807..2fadc443 100644
--- a/docs/hyperdatasets/dataviews.md
+++ b/docs/hyperdatasets/dataviews.md
@@ -132,7 +132,7 @@ may repeat. The settings include the following:
 
 ### Creating Dataviews
 
-Use the [`allegroai.DataView`](google.com) class to create a DataView object. Instantiate DataView objects, specifying 
+Use the `allegroai.DataView` class to create a DataView object. Instantiate DataView objects, specifying 
 iteration settings and additional iteration parameters that control query iterations. 
 
 ```python
@@ -143,7 +143,7 @@ myDataView = DataView(iteration_order=IterationOrder.random, iteration_infinite=
 
 ### Adding queries
 
-To add a query to a DataView, use the [`DataView.add_query`](google.com) method and specify Dataset versions, 
+To add a query to a DataView, use the `DataView.add_query` method and specify Dataset versions, 
 ROI and / or frame queries, and other criteria. 
 
 The `dataset_name` and `version_name` arguments specify the Dataset Version. The `roi_query` and `frame_query` arguments 
@@ -254,7 +254,7 @@ myDataView.add_query(dataset_name='myDataset',
 
 ### Controlling query iteration
 
-Use [`DataView.set_iteration_parameters`](google.com) to manage the order, number, timing, and reproducibility of frames 
+Use `DataView.set_iteration_parameters` to manage the order, number, timing, and reproducibility of frames 
 for training.
 
 
@@ -303,8 +303,8 @@ myDataView.set_iteration_parameters(
 
 ### Debiasing input data
 
-Debias input data using the [DataView.add_query](google.com) method's [weight](google.com) argument to add weights. This 
-is the same [DataView.add_query](google.com) that can be used to specify Dataset versions, and ROI queries and frame queries.
+Debias input data using the `DataView.add_query` method's `weight` argument to add weights. This 
+is the same `DataView.add_query` that can be used to specify Dataset versions, and ROI queries and frame queries.
 
 This example adjusts an imbalance in the input data to improve training for `Car` ROIs that are also `largely occluded` 
 (obstructed). For every frame containing at least one ROI labeled `Car`, approximately five frames containing at least 
@@ -357,7 +357,7 @@ Set label enumeration values to maintain data conformity across multiple codebas
 It is important to set enumeration values for all labels of importance. 
 The default value for labels that are not assigned values is `-1`.
 
-To assign enumeration values for labels use the [`DataView.set_labels`](google.com) method, set a mapping of a label 
+To assign enumeration values for labels use the `DataView.set_labels` method, set a mapping of a label 
 (string) to an integer for ROI labels in a Dataview object.
 
 If certain ROI labels are [mapped](#mapping-roi-labels) from certain labels **to** other labels, 
diff --git a/docs/hyperdatasets/frame_groups.md b/docs/hyperdatasets/frame_groups.md
index 70fc99b4..03923ebc 100644
--- a/docs/hyperdatasets/frame_groups.md
+++ b/docs/hyperdatasets/frame_groups.md
@@ -69,7 +69,7 @@ myVersion.add_frames(frames)
 
 ### Accessing a FrameGroup
 
-To access a FrameGroup, use the [DatasetVersion.get_single_frame](google.com) method, just like when 
+To access a FrameGroup, use the `DatasetVersion.get_single_frame` method, just like when 
 [accessing a SingleFrame](single_frames.md#accessing-singleframes).
 
 ```python
@@ -102,7 +102,7 @@ myVersion.update_frames(frames)
    
 ### Deleting frames
 
-To delete a FrameGroup, use the [DatasetVersion.delete_frames](google.com) method, just like when deleting a 
+To delete a FrameGroup, use the `DatasetVersion.delete_frames` method, just like when deleting a 
 SingleFrame, except that a FrameGroup is being referenced.
 
 ```python
diff --git a/docs/hyperdatasets/single_frames.md b/docs/hyperdatasets/single_frames.md
index 82dfbb02..915ea169 100644
--- a/docs/hyperdatasets/single_frames.md
+++ b/docs/hyperdatasets/single_frames.md
@@ -218,11 +218,11 @@ There are also options to populate the instance with:
 * A dictionary of annotation objects - `annotations`
 * A URI link to a mask file for the frame - `mask_source`
 
-For more information, see [SingleFrame](google.com).
+For more information, see the `SingleFrame` class description.
 
 ### Adding SingleFrames to a Dataset Version
 
-Use the [`DatasetVersion.add_frames`](google.com) method to add SingleFrames to a [Dataset version](dataset.md#dataset-versioning)
+Use the `DatasetVersion.add_frames` method to add SingleFrames to a [Dataset version](dataset.md#dataset-versioning)
 (see [Creating snapshots](dataset.md#creating-snapshots) or [Creating child versions](dataset.md#creating-child-versions)).
 
 ```python
@@ -248,7 +248,7 @@ myDatasetversion.add_frames(frames)
 
 
 ### Accessing SingleFrames
-To access a SingleFrame, use the [DatasetVersion.get_single_frame](google.com) method. 
+To access a SingleFrame, use the `DatasetVersion.get_single_frame` method. 
 
 ```python
 from allegroai import DatasetVersion
@@ -266,9 +266,9 @@ To access a SingleFrame, the following must be specified:
 ### Updating SingleFrames
 
 To update a SingleFrame: 
-* Access the SingleFrame by calling the [DatasetVersion.get_single_frame](google.com) method, 
+* Access the SingleFrame by calling the `DatasetVersion.get_single_frame` method, 
 * Make changes to the frame
-* Update the frame in a DatasetVersion using the [DatasetVersion.update_frames](google.com) method.
+* Update the frame in a DatasetVersion using the `DatasetVersion.update_frames` method.
 
 ```python
 frames = []                
@@ -296,7 +296,7 @@ myDatasetVersion.update_frames(frames)
 
 ### Deleting frames
 
-To delete a SingleFrame, use the [DatasetVersion.delete_frames](google.com) method.
+To delete a SingleFrame, use the `DatasetVersion.delete_frames` method.
 
 ```python
 frames = []                
diff --git a/docs/hyperdatasets/task.md b/docs/hyperdatasets/task.md
index 0091a567..0f2a3179 100644
--- a/docs/hyperdatasets/task.md
+++ b/docs/hyperdatasets/task.md
@@ -21,7 +21,7 @@ task.connect(dataview)
 
 ### Accessing a Task's Dataviews
 
-Use the [Task.get_dataviews](google.com) method to access the Dataviews that are connected to a Task. 
+Use the `Task.get_dataviews` method to access the Dataviews that are connected to a Task. 
 
 ```python
 task.get_dataviews():