diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 45ce00c314830..d95d077e5a67a 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -251,6 +251,8 @@ def apply(self, func, *args, **kwargs) -> Series:
 
         Notes
         -----
+        See :ref:`groupby.apply` in the User Guide for more details and examples.
+
         The resulting dtype will reflect the return value of the passed ``func``,
         see the examples below.
 
@@ -382,6 +384,9 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
 
         Notes
         -----
+        See :ref:`groupby.aggregate` in the User Guide for more details
+        and examples.
+
         When using ``engine='numba'``, there will be no "fall back" behavior internally.
         The group data and group index will be passed as numpy arrays to the JITed
         user defined function, and no alternative execution attempts will be tried.
@@ -711,6 +716,8 @@ def transform(self, func, *args, engine=None, engine_kwargs=None, **kwargs):
 
         Notes
         -----
+        See :ref:`groupby.transform` in the User Guide for more details and examples.
+
         Each group is endowed the attribute 'name' in case you need to know
         which group you are working on.
 
@@ -2180,6 +2187,9 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
 
         Notes
         -----
+        See :ref:`groupby.aggregate` in the User Guide for more details
+        and examples.
+
         When using ``engine='numba'``, there will be no "fall back" behavior internally.
         The group data and group index will be passed as numpy arrays to the JITed
         user defined function, and no alternative execution attempts will be tried.
@@ -2706,6 +2716,8 @@ def transform(self, func, *args, engine=None, engine_kwargs=None, **kwargs):
 
         Notes
         -----
+        See :ref:`groupby.transform` in the User Guide for more details and examples.
+
         Each group is endowed the attribute 'name' in case you need to know
         which group you are working on.
 
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 25f2b76054712..fd8dcb25a4d17 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1541,6 +1541,8 @@ def apply(self, func, *args, include_groups: bool = False, **kwargs) -> NDFrameT
 
         Notes
         -----
+        See :ref:`groupby.apply` in the User Guide for more details and examples.
+
         The resulting dtype will reflect the return value of the passed ``func``,
         see the examples below.