diff --git a/tutorials/Certification_Trainings/Medical_Language_Models/April_2025/Notebooks/Terminology_Demo.ipynb b/tutorials/Certification_Trainings/Medical_Language_Models/April_2025/Notebooks/Terminology_Demo.ipynb
new file mode 100644
index 000000000..483435a2b
--- /dev/null
+++ b/tutorials/Certification_Trainings/Medical_Language_Models/April_2025/Notebooks/Terminology_Demo.ipynb
@@ -0,0 +1,120 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "url = \"demo_url\"\n",
+    "import requests"
+   ]
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "valuesets = requests.get(url + \"/api/valuesets\")\n",
+    "valuesets.json()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vs_metadata = requests.get(url+\"/api/valueset_details/10\")\n",
+    "vs_metadata.json()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-10T14:46:21.924929Z",
+     "start_time": "2025-04-10T14:46:21.918887Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def search_concept(chunks: list, topk: int = 3, vocabulary=[], domain_id=[], search_type=\"\", filter_by_valueset=False, valueset_metadata_ids=[]):\n",
+    "    search_url = url + \"/search\"\n",
+    "    payload = {\"chunks\": chunks,\n",
+    "               \"topk\": topk,\n",
+    "               \"vocabulary_id\": vocabulary,\n",
+    "               \"domain_id\": domain_id,\n",
+    "               \"search_type\": search_type,\n",
+    "               \"filter_by_valueset\": filter_by_valueset,\n",
+    "               \"valueset_metadata_ids\": valueset_metadata_ids}\n",
+    "\n",
+    "    result = requests.post(search_url, json=payload)\n",
+    "    return result.json()\n",
+    "\n",
+    "\n",
+    "def search_concept_with_vocabs(chunk: str, vocabulary, target_vocabulary):\n",
+    "    search_url = url + \"/search\"\n",
+    "    result = requests.post(search_url, json={\"chunks\": [chunk],\n",
+    "                                             \"topk\": 1,\n",
+    "                                             \"vocabulary_id\": [vocabulary],\n",
+    "                                             \"source_vocabulary\": vocabulary,\n",
+    "                                             \"target_vocabulary\": target_vocabulary})\n",
+    "    return result.json()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-10T14:47:03.777470Z",
+     "start_time": "2025-04-10T14:47:02.573031Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "search_concept(\n",
+    "    ['hypertension'],\n",
+    "    # domain_id=['Condition'],\n",
+    "    # topk=2,\n",
+    "    # search_type=\"exact\",\n",
+    "    # filter_by_valueset=True,\n",
+    "    # valueset_metadata_ids = [10]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "search_concept_with_vocabs(\"hypertension\", vocabulary=\"ICD10CM\", target_vocabulary=\"UMLS\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/tutorials/Certification_Trainings/Medical_Language_Models/April_2025/Slides/Terminology Server 202504.pdf b/tutorials/Certification_Trainings/Medical_Language_Models/April_2025/Slides/Terminology Server 202504.pdf
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index 000000000..9335021ea
Binary files /dev/null and b/tutorials/Certification_Trainings/Medical_Language_Models/April_2025/Slides/Terminology Server 202504.pdf differ