diff --git a/python/mxnet/ndarray/numpy/random.py b/python/mxnet/ndarray/numpy/random.py
index 9d1a6f9119ee..e67c766c6bdf 100644
--- a/python/mxnet/ndarray/numpy/random.py
+++ b/python/mxnet/ndarray/numpy/random.py
@@ -23,7 +23,7 @@
 from ..ndarray import NDArray
 
 
-__all__ = ['randint', 'uniform', 'normal', "choice", "rand", "multinomial"]
+__all__ = ['randint', 'uniform', 'normal', "choice", "rand", "multinomial", "shuffle"]
 
 
 def randint(low, high=None, size=None, dtype=None, ctx=None, out=None):
@@ -344,3 +344,39 @@ def rand(*size, **kwargs):
     for s in size:
         output_shape += (s,)
     return uniform(0, 1, size=output_shape, **kwargs)
+
+
+def shuffle(x):
+    """
+    Modify a sequence in-place by shuffling its contents.
+
+    This function only shuffles the array along the first axis of a
+    multi-dimensional array. The order of sub-arrays is changed but
+    their contents remain the same.
+
+    Parameters
+    ----------
+    x: ndarray
+        The array or list to be shuffled.
+
+    Returns
+    -------
+    None
+
+    Examples
+    --------
+    >>> arr = np.arange(10)
+    >>> np.random.shuffle(arr)
+    >>> arr
+    array([5., 1., 0., 6., 7., 3., 9., 8., 4., 2.])  # random
+
+    Multi-dimensional arrays are only shuffled along the first axis:
+
+    >>> arr = np.arange(9).reshape((3, 3))
+    >>> np.random.shuffle(arr)
+    >>> arr
+    array([[6., 7., 8.], # random
+           [3., 4., 5.],
+           [0., 1., 2.]])
+    """
+    _npi.shuffle(x, out=x)
diff --git a/python/mxnet/numpy/random.py b/python/mxnet/numpy/random.py
index 1cad4a55c466..ebc24de63282 100644
--- a/python/mxnet/numpy/random.py
+++ b/python/mxnet/numpy/random.py
@@ -20,7 +20,7 @@
 from __future__ import absolute_import
 from ..ndarray import numpy as _mx_nd_np
 
-__all__ = ["randint", "uniform", "normal", "choice", "rand", "multinomial"]
+__all__ = ["randint", "uniform", "normal", "choice", "rand", "multinomial", "shuffle"]
 
 
 def randint(low, high=None, size=None, dtype=None, ctx=None, out=None):
@@ -321,3 +321,39 @@ def rand(*size, **kwargs):
     for s in size:
         output_shape += (s,)
     return _mx_nd_np.random.uniform(0, 1, size=output_shape, **kwargs)
+
+
+def shuffle(x):
+    """
+    Modify a sequence in-place by shuffling its contents.
+
+    This function only shuffles the array along the first axis of a
+    multi-dimensional array. The order of sub-arrays is changed but
+    their contents remain the same.
+
+    Parameters
+    ----------
+    x: ndarray
+        The array or list to be shuffled.
+
+    Returns
+    -------
+    None
+
+    Examples
+    --------
+    >>> arr = np.arange(10)
+    >>> np.random.shuffle(arr)
+    >>> arr
+    array([5., 1., 0., 6., 7., 3., 9., 8., 4., 2.])  # random
+
+    Multi-dimensional arrays are only shuffled along the first axis:
+
+    >>> arr = np.arange(9).reshape((3, 3))
+    >>> np.random.shuffle(arr)
+    >>> arr
+    array([[6., 7., 8.], # random
+           [3., 4., 5.],
+           [0., 1., 2.]])
+    """
+    _mx_nd_np.random.shuffle(x)
diff --git a/python/mxnet/symbol/numpy/random.py b/python/mxnet/symbol/numpy/random.py
index 48bccb64a2b4..94c29f407acc 100644
--- a/python/mxnet/symbol/numpy/random.py
+++ b/python/mxnet/symbol/numpy/random.py
@@ -21,7 +21,7 @@
 from ...context import current_context
 from . import _internal as _npi
 
-__all__ = ['randint', 'uniform', 'normal', 'rand']
+__all__ = ['randint', 'uniform', 'normal', 'rand', 'shuffle']
 
 
 def randint(low, high=None, size=None, dtype=None, ctx=None, out=None):
@@ -288,3 +288,39 @@ def choice(a, size=None, replace=True, p=None, ctx=None, out=None):
             return _npi.choice(a=a, size=size, replace=replace, ctx=ctx, weighted=False, out=out)
         else:
             return _npi.choice(p, a=a, size=size, replace=replace, ctx=ctx, weighted=True, out=out)
+
+
+def shuffle(x):
+    """
+    Modify a sequence in-place by shuffling its contents.
+
+    This function only shuffles the array along the first axis of a
+    multi-dimensional array. The order of sub-arrays is changed but
+    their contents remain the same.
+
+    Parameters
+    ----------
+    x: _Symbol
+        The array or list to be shuffled.
+
+    Returns
+    -------
+    None
+
+    Examples
+    --------
+    >>> arr = np.arange(10)
+    >>> np.random.shuffle(arr)
+    >>> arr
+    array([5., 1., 0., 6., 7., 3., 9., 8., 4., 2.])  # random
+
+    Multi-dimensional arrays are only shuffled along the first axis:
+
+    >>> arr = np.arange(9).reshape((3, 3))
+    >>> np.random.shuffle(arr)
+    >>> arr
+    array([[6., 7., 8.], # random
+           [3., 4., 5.],
+           [0., 1., 2.]])
+    """
+    _npi.shuffle(x, out=x)
diff --git a/src/operator/random/shuffle_op.cc b/src/operator/random/shuffle_op.cc
index 86797c136bab..0f64fbc51449 100644
--- a/src/operator/random/shuffle_op.cc
+++ b/src/operator/random/shuffle_op.cc
@@ -122,7 +122,7 @@ void ShuffleForwardCPU(const nnvm::NodeAttrs& attrs,
 
 NNVM_REGISTER_OP(_shuffle)
 .add_alias("shuffle")
-.add_alias("_np__random_shuffle")
+.add_alias("_npi_shuffle")
 .describe(R"code(Randomly shuffle the elements.
 
 This shuffles the array along the first axis.