diff --git a/docs/sources/programming_dpep.rst b/docs/sources/programming_dpep.rst
index e2da421..650d2c5 100644
--- a/docs/sources/programming_dpep.rst
+++ b/docs/sources/programming_dpep.rst
@@ -37,8 +37,6 @@ to execute your `Numpy*`_ script on GPU usually requires changing just a few lin
    :caption: Your first NumPy code running on GPU
    :name: ex_01_hello_dpnp
 
-.. command-output:: python ./01-hello_dpnp.py
-   :cwd: ../../examples
 
 In this example ``np.asarray()`` creates an array on the default `SYCL*`_ device, which is ``"gpu"`` on systems
 with integrated or discrete GPU (it is ``"cpu"`` on systems that do not have GPU).
@@ -57,8 +55,6 @@ In the following example we create the array ``x`` on the GPU device, and perfor
    :caption: Select device type while creating array
    :name: ex_02_dpnp_device
 
-.. command-output:: python ./02-dpnp_device.py
-   :cwd: ../../examples
 
 Data Parallel Extension for Numba - numba-dpex
 **********************************************
@@ -69,3 +65,9 @@ SIMD instructions, and schedules those in a way that exploits maximum instructio
 The ``numba-dpex`` extension allows to compile and offload data parallel regions to any data parallel device.
 It takes just a few lines to modify your CPU `Numba*`_ script to run on GPU.
 
+.. literalinclude:: ../../examples/03-dpnp2numba-dpex.py
+   :language: python
+   :lines: 27-
+   :caption: Compile dpnp code with numba-dpex
+   :name: ex_03_dpnp2numba_dpex
+
diff --git a/examples/01-hello_dpnp.py b/examples/01-hello_dpnp.py
index 71852fa..8f3a7bd 100644
--- a/examples/01-hello_dpnp.py
+++ b/examples/01-hello_dpnp.py
@@ -28,3 +28,6 @@
 
 x = np.asarray([1, 2, 3])
 y = np.sum(x)
+
+print(y.shape)  # Must be 0-dimensional array
+print(y)  # Expect 6
diff --git a/examples/02-dpnp_device.py b/examples/02-dpnp_device.py
index a004b1d..16fa2dd 100644
--- a/examples/02-dpnp_device.py
+++ b/examples/02-dpnp_device.py
@@ -33,3 +33,4 @@
     print("GPU device is not available")
 
 y = np.sum(x)
+print(y)  # Expect 6
diff --git a/examples/03-dpnp2numba-dpex.py b/examples/03-dpnp2numba-dpex.py
new file mode 100644
index 0000000..f788b53
--- /dev/null
+++ b/examples/03-dpnp2numba-dpex.py
@@ -0,0 +1,41 @@
+# *****************************************************************************
+# Copyright (c) 2022, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+import dpnp as np
+from numba_dpex import njit
+
+
+@njit(parallel=True, fastmath=True)
+def sum(x):
+    return np.sum(x)
+
+
+x = np.empty(3)
+try:
+    x = np.asarray([1, 2, 3], device="gpu")
+except:
+    print("GPU device is not available")
+