diff --git a/MyIA.AI.Notebooks/Probas/PyMC/PyMC-04-Bayesian-Networks.ipynb b/MyIA.AI.Notebooks/Probas/PyMC/PyMC-04-Bayesian-Networks.ipynb
index be4e3223cb..e6626e8f65 100644
--- a/MyIA.AI.Notebooks/Probas/PyMC/PyMC-04-Bayesian-Networks.ipynb
+++ b/MyIA.AI.Notebooks/Probas/PyMC/PyMC-04-Bayesian-Networks.ipynb
@@ -2111,6 +2111,8 @@
     "- Pearl, J. (2000). *Causality: Models, Reasoning, and Inference.* Cambridge University Press. (do-calculus)\n",
     "\n",
     "***\n",
+    "**Navigation** : [<< PyMC-3 (Factor Graphs)](PyMC-03-Factor-Graphs.ipynb) | [PyMC-5 (Causal Inference) >>](PyMC-05-Causal-Inference.ipynb)\n",
+    "\n",
     "**Retour au sommaire** : [Index Probas](../README.md)"
    ]
   },
@@ -2119,6 +2121,8 @@
    "id": "fuse-17",
    "metadata": {},
    "source": [
+    "## Pour aller plus loin\n",
+    "\n",
     "Les réseaux bayésiens structurent les dependances conditionnelles entre variables via un DAG, et permettent l'inférence MCMC exacte (jusqu'a ~20 variables) ou approchee (au-dela).\n",
     "\n",
     "Ce notebook a illustre :\n",
diff --git a/scripts/notebook_tools/twin_pairs.d/probas-4-bayesian-networks/0014-2026-09-28-myia-po-2027-CoursIA-2.yaml b/scripts/notebook_tools/twin_pairs.d/probas-4-bayesian-networks/0014-2026-09-28-myia-po-2027-CoursIA-2.yaml
new file mode 100644
index 0000000000..c7a1ebb9b9
--- /dev/null
+++ b/scripts/notebook_tools/twin_pairs.d/probas-4-bayesian-networks/0014-2026-09-28-myia-po-2027-CoursIA-2.yaml
@@ -0,0 +1,6 @@
+date: '2026-09-28'
+by: myia-po-2027:CoursIA-2
+python_sha: e6626e8f65894dbf8fde0544e0cf69f5f8b8a960
+csharp_sha: 7ef2d50f2dcddfb3024681fbc29090726fc2b820
+content_python_sha: 75815668c500ebc2d5a5e48aca688ea3970ef681838adc6e8d629e77a0726f45
+content_csharp_sha: ba77fc9181856b651a433cca726ef3c461b2c9369628f3068b7db92bf2a25879