diff --git a/test/Microsoft.ML.Tests/Microsoft.ML.Tests.csproj b/test/Microsoft.ML.Tests/Microsoft.ML.Tests.csproj
index 7360f0f4d0..504b988f82 100644
--- a/test/Microsoft.ML.Tests/Microsoft.ML.Tests.csproj
+++ b/test/Microsoft.ML.Tests/Microsoft.ML.Tests.csproj
@@ -2,6 +2,9 @@
   <PropertyGroup>
     <TargetFramework>netcoreapp2.0</TargetFramework>
   </PropertyGroup>
+  <ItemGroup>
+    <Compile Remove="Scenarios\Api\AspirationalExamples.cs" />
+  </ItemGroup>
 
   <ItemGroup>
     <ProjectReference Include="..\..\src\Microsoft.ML.Ensemble\Microsoft.ML.Ensemble.csproj" />
@@ -28,4 +31,8 @@
   <ItemGroup>
     <PackageReference Include="MlNetMklDeps" Version="$(MlNetMklDepsPackageVersion)" />
   </ItemGroup>
+  
+  <ItemGroup>
+    <None Include="Scenarios\Api\AspirationalExamples.cs" />
+  </ItemGroup>
 </Project>
\ No newline at end of file
diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/AspirationalExamples.cs b/test/Microsoft.ML.Tests/Scenarios/Api/AspirationalExamples.cs
new file mode 100644
index 0000000000..bcb8b7d98f
--- /dev/null
+++ b/test/Microsoft.ML.Tests/Scenarios/Api/AspirationalExamples.cs
@@ -0,0 +1,60 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Microsoft.ML.Tests.Scenarios.Api
+{
+    public class AspirationalExamples
+    {
+        public class IrisPrediction
+        {
+            public string PredictedLabel;
+        }
+
+        public class IrisExample
+        {
+            public float SepalWidth { get; set; }
+            public float SepalLength { get; set; }
+            public float PetalWidth { get; set; }
+            public float PetalLength { get; set; }
+        }
+
+        public void FirstExperienceWithML()
+        {
+            // This is the 'getting started with ML' example, how we see it in our new API.
+            // It currently doesn't compile, let alone work, but we still can discuss and improve the syntax.
+
+            // Load the data into the system.
+            string dataPath = "iris-data.txt";
+            var data = TextReader.FitAndRead(env, dataPath, row => (
+                Label: row.ReadString(0),
+                SepalWidth: row.ReadFloat(1),
+                SepalLength: row.ReadFloat(2),
+                PetalWidth: row.ReadFloat(3),
+                PetalLength: row.ReadFloat(4)));
+
+
+            var preprocess = data.Schema.MakeEstimator(row => (
+                // Convert string label to key.
+                Label: row.Label.DictionarizeLabel(),
+                // Concatenate all features into a vector.
+                Features: row.SepalWidth.ConcatWith(row.SepalLength, row.PetalWidth, row.PetalLength)));
+
+            var pipeline = preprocess
+                // Append the trainer to the training pipeline.
+                .AppendEstimator(row => row.Label.PredictWithSdca(row.Features))
+                .AppendEstimator(row => row.PredictedLabel.KeyToValue());
+
+            // Train the model and make some predictions.
+            var model = pipeline.Fit<IrisExample, IrisPrediction>(data);
+
+            IrisPrediction prediction = model.Predict(new IrisExample
+                {
+                    SepalWidth = 3.3f,
+                    SepalLength = 1.6f,
+                    PetalWidth = 0.2f,
+                    PetalLength = 5.1f
+                });
+        }
+    }
+}