diff --git a/notebooks/numpy_cours.ipynb b/notebooks/numpy_cours.ipynb
index fe632fbd4ddb438dd5d3543aec7b68b374844ed9..19ff1ffcc87c622ea13515b3df5a1a339afae67b 100644
--- a/notebooks/numpy_cours.ipynb
+++ b/notebooks/numpy_cours.ipynb
@@ -1033,6 +1033,171 @@
     "> Python language has its own random module but numpy has more functionalities."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "e73ecd23-a1eb-47ef-be1f-f92130547340",
+   "metadata": {},
+   "source": [
+    "First you have to create a Generator object, usualy by using the default_rng function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8e18d829-b9e4-4880-b35e-a96fc713d95f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rng = np.random.default_rng() "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "55fbac7f-33d1-4108-9f50-6aaf6db640a7",
+   "metadata": {},
+   "source": [
+    "then use random methods"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "81be533a-3beb-4af8-9e26-69ad5d44e41d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9770692753749981"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Generate one random float uniformly distributed over the range [0, 1)\n",
+    "rng.random() # result below may vary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f085514b-5fcd-4112-a045-23eb6f6f3e5c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 1.73553135,  0.22361916, -0.73362824, -0.33249582, -0.72058886,\n",
+       "       -0.27996662, -0.34853205, -2.27085731, -0.80546885,  1.42012754])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# array of normally distributed values\n",
+    "# with mean=0 (loc) and std=1.0 (scale) (defaults)\n",
+    "rng.normal(loc=0.0, scale=1.0, size=10)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "9dcf97f4-1984-4739-a49a-9c9c7a7d4a98",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-0.25121824, -1.50960959],\n",
+       "       [ 1.20405797,  1.76066421],\n",
+       "       [ 1.00618911,  1.00338646],\n",
+       "       [ 0.33048819,  3.14524965],\n",
+       "       [ 4.26693195,  1.77804119]])"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# a 2Darray of normally distributed values\n",
+    "rng.normal(loc=1.0, scale=2.0, size=(5,2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "8faa1d85-e2cf-482f-af13-1a339f85b273",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1.47566294, 1.66996391, 0.97314979, 0.11779833, 1.43473446,\n",
+       "       0.21334751, 0.67050575, 1.75677774, 0.95711036, 0.97817719])"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# array of uniform distributed values\n",
+    "rng.uniform(low=0, high=2, size=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "3494d529-5fef-47ef-9014-64b6d3d69244",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.08564916714362436"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# you can specify a seed when you build a random generator\n",
+    "s_rng = np.random.default_rng(seed=3)\n",
+    "\n",
+    "s_rng.random()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d2948e4-3d1e-4c22-b5e9-b92889282bf5",
+   "metadata": {},
+   "source": [
+    "* https://numpy.org/doc/stable/reference/random/index.html\n",
+    "* https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.default_rng\n",
+    "* https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2c0eea6a-b4d2-4c28-9674-af82879f6101",
+   "metadata": {},
+   "source": [
+    "## old way to generate random values\n",
+    "\n",
+    "These functions will be deprecated soon"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 36,
@@ -2958,7 +3123,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,