diff --git a/shiny/templates/app-templates/dashboard/app-core.py b/shiny/templates/app-templates/dashboard/app-core.py
index 3e83227e0..341dda69d 100644
--- a/shiny/templates/app-templates/dashboard/app-core.py
+++ b/shiny/templates/app-templates/dashboard/app-core.py
@@ -29,21 +29,17 @@ def make_value_box(penguin):
             "species", "Filter by species", species, selected=species
         ),
     ),
-    ui.row(
-        ui.layout_columns(
-            *[make_value_box(penguin) for penguin in species],
-        )
+    ui.layout_columns(
+        *[make_value_box(penguin) for penguin in species],
     ),
-    ui.row(
-        ui.layout_columns(
-            ui.card(
-                ui.card_header("Summary statistics"),
-                ui.output_data_frame("summary_statistics"),
-            ),
-            ui.card(
-                ui.card_header("Penguin bills"),
-                ui.output_plot("length_depth"),
-            ),
+    ui.layout_columns(
+        ui.card(
+            ui.card_header("Summary statistics"),
+            ui.output_data_frame("summary_statistics"),
+        ),
+        ui.card(
+            ui.card_header("Penguin bills"),
+            ui.output_plot("length_depth"),
         ),
     ),
 )
diff --git a/shiny/templates/app-templates/dashboard/app-express.py b/shiny/templates/app-templates/dashboard/app-express.py
new file mode 100644
index 000000000..b5e0f7153
--- /dev/null
+++ b/shiny/templates/app-templates/dashboard/app-express.py
@@ -0,0 +1,82 @@
+from pathlib import Path
+
+import pandas as pd
+import seaborn as sns
+
+from shiny import reactive
+from shiny.express import input, render, ui
+
+sns.set_theme(style="white")
+df = pd.read_csv(Path(__file__).parent / "penguins.csv", na_values="NA")
+species = ["Adelie", "Gentoo", "Chinstrap"]
+
+ui.page_opts(fillable=True)
+
+
+def count_species(df, species):
+    return df[df["Species"] == species].shape[0]
+
+
+with ui.sidebar():
+    ui.input_slider("mass", "Mass", 2000, 6000, 3400)
+    ui.input_checkbox_group("species", "Filter by species", species, selected=species)
+
+
+@reactive.Calc
+def filtered_df() -> pd.DataFrame:
+    filt_df = df[df["Species"].isin(input.species())]
+    filt_df = filt_df.loc[filt_df["Body Mass (g)"] > input.mass()]
+    return filt_df
+
+
+with ui.layout_columns():
+    with ui.value_box(theme="primary"):
+        "Adelie"
+
+        @render.text
+        def adelie_count():
+            return count_species(filtered_df(), "Adelie")
+
+    with ui.value_box(theme="primary"):
+        "Gentoo"
+
+        @render.text
+        def gentoo_count():
+            return count_species(filtered_df(), "Gentoo")
+
+    with ui.value_box(theme="primary"):
+        "Chinstrap"
+
+        @render.text
+        def chinstrap_count():
+            return count_species(filtered_df(), "Chinstrap")
+
+
+with ui.layout_columns():
+    with ui.card():
+        ui.card_header("Summary statistics")
+
+        @render.data_frame
+        def summary_statistics():
+            display_df = filtered_df()[
+                [
+                    "Species",
+                    "Island",
+                    "Bill Length (mm)",
+                    "Bill Depth (mm)",
+                    "Body Mass (g)",
+                ]
+            ]
+            return render.DataGrid(display_df, filters=True)
+
+    with ui.card():
+        ui.card_header("Penguin bills")
+
+        @render.plot
+        def length_depth():
+            return sns.scatterplot(
+                data=filtered_df(),
+                x="Bill Length (mm)",
+                y="Bill Depth (mm)",
+                hue="Species",
+            )