diff --git a/tutorials/Tutorial4_FAQ_style_QA.ipynb b/tutorials/Tutorial4_FAQ_style_QA.ipynb
index 587f440d6..14caa141f 100644
--- a/tutorials/Tutorial4_FAQ_style_QA.ipynb
+++ b/tutorials/Tutorial4_FAQ_style_QA.ipynb
@@ -186,6 +186,7 @@
     "# Get embeddings for our questions from the FAQs\n",
     "questions = list(df[\"question\"].values)\n",
     "df[\"question_emb\"] = retriever.embed_queries(texts=questions)\n",
+    "df[\"question_emb\"] = df[\"question_emb\"].apply(list) # convert from numpy to list for ES indexing\n",
     "\n",
     "# Convert Dataframe to list of dicts and index them in our DocumentStore\n",
     "docs_to_index = df.to_dict(orient=\"records\")\n",
diff --git a/tutorials/Tutorial4_FAQ_style_QA.py b/tutorials/Tutorial4_FAQ_style_QA.py
index c1d949486..6b8268565 100755
--- a/tutorials/Tutorial4_FAQ_style_QA.py
+++ b/tutorials/Tutorial4_FAQ_style_QA.py
@@ -68,6 +68,7 @@ print(df.head())
 # Get embeddings for our questions from the FAQs
 questions = list(df["question"].values)
 df["question_emb"] = retriever.embed_queries(texts=questions)
+df["question_emb"] = df["question_emb"].apply(list) # convert from numpy to list for ES indexing
 
 # Convert Dataframe to list of dicts and index them in our DocumentStore
 docs_to_index = df.to_dict(orient="records")