diff --git a/.github/test/scripts/check_cell_output.py b/.github/test/scripts/check_cell_output.py
new file mode 100644
index 0000000000..54934e9ab0
--- /dev/null
+++ b/.github/test/scripts/check_cell_output.py
@@ -0,0 +1,102 @@
+# This is used in notebook validation to check the output of individual cells of the notebook.
+# The parameters are:
+# 	--file_name              The name of the notebook output file
+#       --folder                 The path for the folder containing the notebook output.
+#       --expected_stdout        The expected output
+#       --cell_source            Option cell source to be checked
+#       --cell_output_substring  The specified cell is checked for this output.
+#       --check_widget           True indicates that the widget output should be checked.
+
+import json
+import os
+import argparse
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--file_name")
+parser.add_argument("--folder")
+parser.add_argument("--expected_stdout", nargs="*")
+parser.add_argument("--cell_source", nargs="*")
+parser.add_argument("--cell_output_substring")
+parser.add_argument("--check_widget", type=bool)
+
+inputArgs = parser.parse_args()
+full_name = os.path.join(inputArgs.folder, inputArgs.file_name)
+
+
+def checkCellOutput(fileName, expected_stdout):
+    notebook = json.load(open(fileName, "r"))
+    code_cells = (cell for cell in notebook["cells"] if cell["cell_type"] == "code")
+    for cell, expected_output in zip(code_cells, expected_stdout):
+        source = cell["source"]
+        print("Checking cell starting with: " + source[0])
+        for actual_output in cell["outputs"]:
+            if "text" in actual_output:
+                actual_output_text = actual_output["text"]
+                for actual_line, expected_line in zip(
+                    actual_output_text, expected_output
+                ):
+                    assert actual_line.startswith(expected_line), (
+                        'Actual Line "'
+                        + actual_line
+                        + '" didn\'t match "'
+                        + expected_line
+                        + '"'
+                    )
+                assert len(actual_output_text) == len(expected_output), (
+                    "Actual output length = "
+                    + str(len(actual_output_text))
+                    + ", expected_length - "
+                    + str(len(expected_output))
+                )
+    print("checkCellOutput completed")
+
+
+def checkSpecifiedCellOutput(fileName, cell_source, cell_output_substring):
+    # assert that a specific code cell contains a substring (case insensitve)
+    notebook = json.load(open(fileName, "r"))
+    code_cells = (cell for cell in notebook["cells"] if cell["cell_type"] == "code")
+    msg = (
+        "actual output {} contain expected "
+        "substring:\nactual output = {}\nexpected substring={}"
+    )
+    for cell in code_cells:
+        source = cell["source"]
+        if source != cell_source:
+            continue
+        print("Checking cell starting with: " + source[0])
+        for actual_output in cell["outputs"]:
+            actual_output_str = str(actual_output)
+            bad_msg = msg.format("does not", actual_output_str, cell_output_substring)
+            assert cell_output_substring.lower() in actual_output_str.lower(), bad_msg
+    print("checkSpecifiedCellOutput completed")
+
+
+def checkWidgetOutput(fileName):
+    widget_property = "application/aml.mini.widget.v1"
+    widget_data_found = False
+    notebook = json.load(open(fileName, "r"))
+    code_cells = (cell for cell in notebook["cells"] if cell["cell_type"] == "code")
+    for cell in code_cells:
+        for actual_output in cell["outputs"]:
+            if "data" in actual_output:
+                actual_output_data = actual_output["data"]
+                if widget_property in actual_output_data:
+                    print("Widget data found")
+                    widget_data = actual_output_data[widget_property]
+                    assert widget_data.startswith('{"status": "Completed"'), widget_data
+                    print("Widget data valid")
+                    widget_data_found = True
+    assert widget_data_found
+    print("checkWidgetOutput completed")
+
+
+if inputArgs.expected_stdout is not None:
+    checkCellOutput(full_name, inputArgs.expected_stdout)
+
+if inputArgs.cell_source is not None:
+    checkSpecifiedCellOutput(
+        full_name, inputArgs.cell_source, inputArgs.cell_output_substring
+    )
+
+if inputArgs.check_widget:
+    checkWidgetOutput(full_name)
diff --git a/.github/test/scripts/check_experiment_result.py b/.github/test/scripts/check_experiment_result.py
new file mode 100644
index 0000000000..38b0cf8fb4
--- /dev/null
+++ b/.github/test/scripts/check_experiment_result.py
@@ -0,0 +1,295 @@
+# This is used to check the results for an experiment
+# The parameters are:
+# 	--experiment_name            The name of the experiment to check
+# 	--file_name                  The name of the notebook output file
+#       --folder                     The notebook folder
+#       --metric_name                The name of the metric to check
+#       --expected_num_iteration     The expected number of iterations.
+#       --minimum_median_score       The minimum expected median score.
+#       --absolute_minimum_score     The absolute minimum expected score.
+#       --maximum_median_score       The maximum expected median score.
+#       --absolute_maximum_score     The absolute maximum expected score.
+#       --expected_run_count         The expected number of runs.
+#       --vision_train_run           Indicates that this is a vission run.
+#       --check_explanation_best_run Check the explanation of the best run.
+#       --is_local_run               Indicates that this is a local run.
+
+import argparse
+import os
+from azureml.core.experiment import Experiment
+from azureml.core.workspace import Workspace
+from azureml.train.automl.run import AutoMLRun
+from azureml.core.run import Run
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--experiment_name")
+parser.add_argument("--file_name")
+parser.add_argument("--folder")
+parser.add_argument("--metric_name")
+parser.add_argument("--expected_num_iteration", type=int)
+parser.add_argument("--minimum_median_score", type=float)
+parser.add_argument("--absolute_minimum_score", type=float)
+parser.add_argument("--maximum_median_score", type=float)
+parser.add_argument("--absolute_maximum_score", type=float)
+parser.add_argument("--expected_run_count", type=int)
+parser.add_argument("--vision_train_run", type=bool)
+parser.add_argument("--check_explanation_best_run", type=bool)
+parser.add_argument("--is_local_run", type=bool)
+
+inputArgs = parser.parse_args()
+
+try:
+    from azureml.interpret import ExplanationClient
+except ImportError:
+    print(
+        "azureml-interpret could not be imported for validation, not installed locally, skipping..."
+    )
+
+
+def checkExperimentResult(
+    experiment_name,
+    file_name,
+    folder,
+    metric_name=None,
+    expected_num_iteration=None,
+    minimum_median_score=None,
+    absolute_minimum_score=0.0,
+    maximum_median_score=1.0,
+    absolute_maximum_score=1.0,
+    expected_run_count=1,
+    vision_train_run=False,
+):
+    ws = Workspace.from_config(folder)
+    experiment = Experiment(ws, experiment_name)
+    runs = list(experiment.get_runs(type="automl"))
+
+    print("Total runs: " + str(len(runs)))
+
+    runs = getNotebookRuns(runs, file_name, folder)
+
+    if vision_train_run:
+        # Only check the most recent runs
+        error_msg = (
+            "Not enough runs found in " + ws.name + " for experiment " + experiment_name
+        )
+        assert len(runs) >= expected_run_count, error_msg
+        runs = runs[:expected_run_count]
+    print("Run count: {}".format(len(runs)))
+    assert len(runs) == expected_run_count
+
+    for run in runs:
+        print("Validating run: " + run.id)
+        status = run.get_details()
+        ml_run = AutoMLRun(experiment=experiment, run_id=run.id)
+        children = list(ml_run.get_children())
+
+        if vision_train_run:
+            checkVisionTrainRun(children, minimum_median_score, maximum_median_score)
+        else:
+            properties = ml_run.get_properties()
+            status = ml_run.get_details()
+            print("Number of iterations found = " + properties["num_iterations"])
+            assert properties["num_iterations"] == str(expected_num_iteration)
+            badScoreCount = 0
+            goodScoreCount = 0
+            # run_metrics = ml_run.get_metrics(recursive=True)
+
+            for iteration in children:
+                iteration_status = iteration.status
+                print(iteration.id + ": " + iteration_status)
+                assert iteration_status == "Completed" or iteration_status == "Canceled"
+                if iteration_status == "Completed":
+                    props = iteration.get_properties()
+                    if props.get("runTemplate") != "automl_child":
+                        # not training iteration
+                        continue
+                    metrics = iteration.get_metrics()
+                    print(metric_name + " = " + str(metrics[metric_name]))
+                    assert metrics[metric_name] >= absolute_minimum_score
+                    assert metrics[metric_name] <= absolute_maximum_score
+                    if (
+                        metrics[metric_name] < minimum_median_score
+                        or metrics[metric_name] > maximum_median_score
+                    ):
+                        badScoreCount += 1
+                    else:
+                        goodScoreCount += 1
+            assert badScoreCount < goodScoreCount
+        print("Run status: " + status["status"])
+        assert status["status"] == "Completed"
+    print("check_experiment_result complete")
+
+
+def check_experiment_model_explanation_of_best_run(
+    experiment_name, file_name, folder, is_local_run=False
+):
+    print("Start running check_experiment_model_explanation_of_best_run().")
+    ws = Workspace.from_config(folder)
+
+    experiment = Experiment(ws, experiment_name)
+    automl_runs = list(experiment.get_runs(type="automl"))
+    automl_runs = getNotebookRuns(automl_runs, file_name, folder)
+
+    for run in automl_runs:
+        print("Validating run: " + run.id)
+        ml_run = AutoMLRun(experiment=experiment, run_id=run.id)
+
+        if not is_local_run:
+            model_explainability_run_id = ml_run.id + "_" + "ModelExplain"
+            print("Checking the Model Explanation run: " + model_explainability_run_id)
+            # Wait for the ME run to complete before accessing the result.
+            model_explainability_run = Run(
+                experiment=experiment, run_id=model_explainability_run_id
+            )
+            model_explainability_run.wait_for_completion()
+
+        # The best run should have explanation result.
+        best_run = ml_run.get_best_child()
+        expl_client = ExplanationClient.from_run(best_run)
+
+        # Download the engineered explanations
+        engineered_explanations = expl_client.download_model_explanation(raw=False)
+        assert engineered_explanations is not None
+        importance_dict = engineered_explanations.get_feature_importance_dict()
+        # Importance dict should not be empty.
+        assert importance_dict is not None and importance_dict
+
+        # Download the raw explanations
+        raw_explanations = expl_client.download_model_explanation(raw=True)
+        assert raw_explanations is not None
+        importance_dict = raw_explanations.get_feature_importance_dict()
+        # Importance dict should not be empty.
+        assert importance_dict is not None and importance_dict
+
+    print("check_experiment_model_explanation_of_best_run() completed.")
+
+
+def checkVisionTrainRun(child_runs, expected_min_score, expected_max_score):
+    for hd_run in child_runs:
+        print(hd_run.id + ": " + hd_run.status)
+        assert hd_run.status == "Completed"
+
+        _, best_metric = hd_run._get_best_run_and_metric_value(
+            include_failed=False, include_canceled=False
+        )
+        print("Primary metric value of {}: {}".format(hd_run.id, best_metric))
+
+        lower_err_msg = (
+            "Primary metric value was lower than the expected min value of {}".format(
+                expected_min_score
+            )
+        )
+        higher_err_msg = (
+            "Primary metric value was higher than the expected max value of {}".format(
+                expected_max_score
+            )
+        )
+        assert best_metric >= expected_min_score, lower_err_msg
+        assert best_metric <= expected_max_score, higher_err_msg
+
+
+def checkVisionScoreRun(
+    experiment_name,
+    min_map_score=0.0,
+    max_map_score=0.0,
+    min_precision_score=0.0,
+    max_precision_score=0.0,
+    min_recall_score=0.0,
+    max_recall_score=0.0,
+    expected_run_count=1,
+):
+    ws = Workspace.from_config()
+    experiment = Experiment(ws, experiment_name)
+    runs = list(experiment.get_runs(type="azureml.scriptrun"))
+
+    error_msg = (
+        "Not enough runs found in " + ws.name + " for experiment " + experiment_name
+    )
+    assert len(runs) >= expected_run_count, error_msg
+    runs = runs[:expected_run_count]
+    print("azureml.scriptrun run type count: {}".format(len(runs)))
+    assert len(runs) == expected_run_count
+
+    for run in runs:
+        print("Validating run: " + run.id)
+        status = run.get_details()
+
+        # Validation only implemented for object detection
+        if experiment_name == "flickr47-logo-detection":
+            metrics = run.get_metrics()
+            checkMetric(
+                metrics,
+                run_id=run.id,
+                metric_name="map",
+                expected_min=min_map_score,
+                expected_max=max_map_score,
+            )
+            checkMetric(
+                metrics,
+                run_id=run.id,
+                metric_name="precision",
+                expected_min=min_precision_score,
+                expected_max=max_precision_score,
+            )
+            checkMetric(
+                metrics,
+                run_id=run.id,
+                metric_name="recall",
+                expected_min=min_recall_score,
+                expected_max=max_recall_score,
+            )
+
+        print("Run status: " + status["status"])
+        assert status["status"] == "Completed"
+    print("checkVisionScoreRun complete")
+
+
+def checkMetric(metrics, run_id, metric_name, expected_min, expected_max):
+    score = metrics[metric_name]
+    print("{} score of {}: {}".format(metric_name, run_id, score))
+
+    lower_err_msg = "{} value was lower than the expected min value of {}".format(
+        metric_name, expected_min
+    )
+    higher_err_msg = "{} value was higher than the expected max value of {}".format(
+        metric_name, expected_max
+    )
+    assert score >= expected_min, lower_err_msg
+    assert score <= expected_max, higher_err_msg
+
+
+def getNotebookRuns(runs, file_name, folder):
+    full_name = os.path.join(folder, file_name)
+    notebook_runs = []
+
+    with open(full_name, "r") as notebook_file:
+        notebook_output = notebook_file.read()
+
+        for run in runs:
+            if run.id in notebook_output:
+                notebook_runs.append(run)
+
+    return notebook_runs
+
+
+checkExperimentResult(
+    inputArgs.experiment_name,
+    inputArgs.file_name,
+    inputArgs.folder,
+    inputArgs.metric_name,
+    inputArgs.expected_num_iteration or 1000,
+    inputArgs.minimum_median_score,
+    inputArgs.absolute_minimum_score or 0.0,
+    inputArgs.maximum_median_score or 1.0,
+    inputArgs.absolute_maximum_score or 1.0,
+    inputArgs.expected_run_count or 1,
+    inputArgs.vision_train_run,
+)
+
+if inputArgs.check_explanation_best_run:
+    check_experiment_model_explanation_of_best_run(
+        inputArgs.experiment_name,
+        inputArgs.file_name,
+        inputArgs.folder,
+        inputArgs.is_local_run,
+    )
diff --git a/.github/test/scripts/check_notebook_output.py b/.github/test/scripts/check_notebook_output.py
new file mode 100644
index 0000000000..471580797b
--- /dev/null
+++ b/.github/test/scripts/check_notebook_output.py
@@ -0,0 +1,115 @@
+# This is used in notebook validation to check the output cells of the notebook.
+# It checks for unexpected warnings or errors
+# The parameters are:
+# 	--file_name   The name of the notebook output file
+#       --folder      The path for the folder containing the notebook output.
+#       --check       A list of strings to check for.
+#                     stderr indicates anything written to stderr.
+
+import json
+import requests
+import os
+import argparse
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--file_name")
+parser.add_argument("--folder")
+parser.add_argument("--check", nargs="+")
+
+inputArgs = parser.parse_args()
+full_name = os.path.join(inputArgs.folder, inputArgs.file_name)
+
+allowed_list = [
+    "UserWarning: Matplotlib is building the font cache",
+    "UserWarning: Starting from version 2.2.1",
+    "the library file in distribution wheels for macOS is built by the Apple Clang",
+    "brew install libomp",
+    "No verified requirements file found" "failed to create lock file",
+    "retrying",
+    "Using default datastore for uploads",
+    "Already registered authentication for run id",
+    "INFO - Initializing logging file for interpret-community",
+    "INFO:interpret_community.common.explanation_utils:Using default datastore for uploads",
+    "better speed can be achieved with apex",
+    "numExpr defaulting to",
+    "no version information available",
+    "Falling back to use azure cli login credentials",
+    "recommend to use ServicePrincipalAuthentication or MsiAuthentication",
+    "Please refer to aka.ms/aml-notebook-auth",
+    "Class KubernetesCompute: This is an experimental class",
+    "Class SynapseCompute: This is an experimental class",
+    'Please use "Dataset.File.upload_directory"',
+    'Please use "FileDatasetFactory.upload_directory" instead',
+    "Called AzureBlobDatastore.upload_files",
+    "LinkTabularOutputDatasetConfig",
+    "This may take a few minutes",
+    "Downloading dataset",
+    "logger.warning",
+    "Importing plotly failed",
+    "Found the config file in:",
+    "Check: endpoint",
+    "data_collector is not a known attribute of class",
+    "Readonly attribute primary_metric will be ignored",
+    "Downloading artifact",
+    "The progress bar can be disabled by setting the environment variable MLFLOW_ENABLE_ARTIFACTS_PROGRESS_BAR",
+    "Warnings:",
+    "Downloading builder script",
+    "Downloading extra modules",
+    "custom base image or base dockerfile detected",
+    "TqdmWarning: IProgress not found.",
+    "from .autonotebook import tqdm as notebook_tqdm",
+    "Class AutoDeleteSettingSchema: This is an experimental class",
+    "Class AutoDeleteConditionSchema: This is an experimental class",
+    "Class BaseAutoDeleteSettingSchema: This is an experimental class",
+    "Class IntellectualPropertySchema: This is an experimental class",
+    "Class ProtectionLevelSchema: This is an experimental class",
+    "Class BaseIntellectualPropertySchema: This is an experimental class",
+    "Class PipelineComponentBatchDeployment: This is an experimental class",
+    "Class LinkTabularOutputDatasetConfig: This is an experimental class",
+    "Field 'max_nodes': This is an experimental field",
+    "Uploading ",
+    "Forecasting parameter ",
+    "Parameter ",
+    "Get_data scripts will be deprecated",
+    "cost_mode is an internal parameter",
+    "save_mlflow is an internal parameter",
+    "start_auxiliary_runs_before_parent_complete is an internal parameter",
+    "Detected ",
+]
+
+with open(full_name, "r") as notebook_file:
+    notebook = json.load(notebook_file)
+
+    for cell in notebook["cells"]:
+        if cell["cell_type"] == "code":
+            for output in cell["outputs"]:
+                if "text" in output:
+                    for line in output["text"]:
+                        # Avoid failing notebook runs on empty
+                        # warnings.
+                        if not line.strip():
+                            continue
+                        for not_allowed in inputArgs.check:
+                            lower_line = line.lower()
+                            if not_allowed == "stderr":
+                                if "name" in output:
+                                    assert output["name"] != "stderr" or any(
+                                        (a.lower() in lower_line) for a in allowed_list
+                                    ), (
+                                        "Found stderr line:\n"
+                                        + line
+                                        + "\n in file "
+                                        + inputArgs.file_name
+                                    )
+                            else:
+                                assert not_allowed.lower() not in lower_line or any(
+                                    (a.lower() in lower_line) for a in allowed_list
+                                ), (
+                                    not_allowed
+                                    + " found in line:\n"
+                                    + line
+                                    + "\n in file "
+                                    + inputArgs.file_name
+                                )
+
+print("check notebook output completed")
diff --git a/.github/test/scripts/check_timeseries.py b/.github/test/scripts/check_timeseries.py
new file mode 100644
index 0000000000..793fabbbf5
--- /dev/null
+++ b/.github/test/scripts/check_timeseries.py
@@ -0,0 +1,96 @@
+# This is used to check the results for a historical time series experiment
+# The parameters are:
+# 	--experiment_name            The name of the experiment to check
+# 	--file_name                  The name of the notebook output file
+#       --folder                     The notebook folder
+
+import sys
+import argparse
+import os
+
+from azureml.core.experiment import Experiment
+from azureml.core.workspace import Workspace
+from azureml.train.automl.run import AutoMLRun
+from azureml.core.run import Run
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--experiment_name")
+parser.add_argument("--file_name")
+parser.add_argument("--folder")
+
+inputArgs = parser.parse_args()
+
+
+def get_hts_run_type(run):
+    children = list(run.get_children())
+    return children[1].type
+
+
+def check_training_run(step_runs, pipeline_run):
+    assert len(step_runs) == 6, "HTS training runs {} should have 6 steps.".format(
+        pipeline_run.id
+    )
+    automl_parents = []
+    for step in step_runs:
+        if step.name == "hts-automl-training":
+            print("Checking AutoML runs for pipeline {}".format(pipeline_run.id))
+            automl_parents = list(step.get_children())
+            for automl in automl_parents:
+                assert (
+                    automl.status == "Completed"
+                ), "AutoML run {} should be in Completed state.".format(automl.id)
+    assert (
+        len(automl_parents) > 0
+    ), "Run {} should have at least one automl run.".format(pipeline_run.id)
+
+
+def check_hts_experiment(experiment_name, file_name, folder):
+    ws = Workspace.from_config(folder)
+    experiment = Experiment(ws, experiment_name)
+    runs = list(experiment.get_runs())
+    runs = getNotebookRuns(runs, file_name, folder)
+
+    assert len(runs) > 0, "At least one pipelines needs to be triggered."
+    n_hts_training = 0
+    n_hts_inferencing = 0
+    for r in runs:
+        print("Checking pipeline run {}".format(r.id))
+        assert r.status == "Completed", "Run {} should be in Completed state.".format(
+            r.id
+        )
+        assert r.type == "azureml.PipelineRun", "Run {} should be pipeline run.".format(
+            r.id
+        )
+        step_runs = list(r.get_children())
+        print("Checking all steps status now for {}.".format(r.id))
+        for s in step_runs:
+            assert (
+                s.status == "Completed"
+            ), "Run {} of {} should be in Completed state.".format(s.id, r.id)
+        if get_hts_run_type(r) == "azureml.HTSInferencing":
+            print("Checking inferencing run.")
+            n_hts_inferencing += 1
+            assert (
+                len(step_runs) == 3
+            ), "Inferencing run {} should have 3 steps.".format(r.id)
+        elif get_hts_run_type(r) == "azureml.HTSTraining":
+            print("Checking training run.")
+            n_hts_training += 1
+            check_training_run(step_runs, r)
+
+
+def getNotebookRuns(runs, file_name, folder):
+    full_name = os.path.join(folder, file_name)
+    notebook_runs = []
+
+    with open(full_name, "r") as notebook_file:
+        notebook_output = notebook_file.read()
+
+        for run in runs:
+            if run.id in notebook_output:
+                notebook_runs.append(run)
+
+    return notebook_runs
+
+
+check_hts_experiment(inputArgs.experiment_name, inputArgs.file_name, inputArgs.folder)
diff --git a/.github/test/scripts/check_v2_experiment_result.py b/.github/test/scripts/check_v2_experiment_result.py
new file mode 100644
index 0000000000..9f5c490040
--- /dev/null
+++ b/.github/test/scripts/check_v2_experiment_result.py
@@ -0,0 +1,161 @@
+# This is used to check the results for an experiment
+# The parameters are:
+# 	--experiment_name            The name of the experiment to check
+# 	--file_name                  The name of the notebook output file
+#       --folder                     The notebook folder
+#       --metric_name                The name of the metric to check
+#       --expected_num_iteration     The expected number of iterations.
+#       --minimum_median_score       The minimum expected median score.
+#       --absolute_minimum_score     The absolute minimum expected score.
+#       --maximum_median_score       The maximum expected median score.
+#       --absolute_maximum_score     The absolute maximum expected score.
+#       --expected_run_count         The expected number of runs.
+#       --vision_train_run           Indicates that this is a vission run.
+#       --check_explanation_best_run Check the explanation of the best run.
+#       --is_local_run               Indicates that this is a local run.
+
+import argparse
+import mlflow
+import os
+from mlflow.entities import ViewType
+from mlflow.tracking.client import MlflowClient
+from azure.identity import AzureCliCredential
+from azure.ai.ml import automl, Input, MLClient, command
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--experiment_name")
+parser.add_argument("--file_name")
+parser.add_argument("--folder")
+parser.add_argument("--metric_name")
+parser.add_argument("--expected_num_iteration", type=int)
+parser.add_argument("--minimum_median_score", type=float)
+parser.add_argument("--absolute_minimum_score", type=float)
+parser.add_argument("--maximum_median_score", type=float)
+parser.add_argument("--absolute_maximum_score", type=float)
+parser.add_argument("--expected_run_count", type=int)
+parser.add_argument("--vision_train_run", type=bool)
+parser.add_argument("--check_explanation_best_run", type=bool)
+parser.add_argument("--is_local_run", type=bool)
+
+inputArgs = parser.parse_args()
+
+
+def checkExperimentResult(
+    experiment_name,
+    file_name,
+    folder,
+    metric_name=None,
+    expected_num_iteration=None,
+    minimum_median_score=None,
+    absolute_minimum_score=0.0,
+    maximum_median_score=1.0,
+    absolute_maximum_score=1.0,
+    expected_run_count=1,
+    vision_train_run=False,
+):
+    credential = AzureCliCredential()
+    ml_client = MLClient.from_config(credential)
+
+    MLFLOW_TRACKING_URI = ml_client.workspaces.get(
+        name=ml_client.workspace_name
+    ).mlflow_tracking_uri
+
+    mlflow.set_tracking_uri(MLFLOW_TRACKING_URI)
+
+    mlflow_client = MlflowClient()
+
+    experiment = mlflow_client.get_experiment_by_name(experiment_name)
+
+    print("Experimentid = " + experiment.experiment_id)
+
+    runs = mlflow_client.search_runs(
+        experiment_ids=experiment.experiment_id,
+        filter_string="",
+        run_view_type=ViewType.ALL,
+        order_by=["run.info.start_time DESC"],
+    )
+
+    print("Total runs: " + str(len(runs)))
+
+    root_run_ids = getNotebookRuns(runs, file_name, folder)
+
+    print("root_run_ids: " + str(root_run_ids))
+
+    if vision_train_run:
+        # Only check the most recent runs
+        error_msg = (
+            "Not enough runs found in " + ws.name + " for experiment " + experiment_name
+        )
+        assert len(root_run_ids) >= expected_run_count, error_msg
+        runs = runs[:expected_run_count]
+    print("Run count: {}".format(len(root_run_ids)))
+    assert len(root_run_ids) == expected_run_count
+
+    for root_run_id in root_run_ids:
+        print("Validating run: " + root_run_id)
+        children = getChildRuns(runs, root_run_id)
+
+        if not vision_train_run:
+            badScoreCount = 0
+            goodScoreCount = 0
+            # run_metrics = ml_run.get_metrics(recursive=True)
+
+            for iteration in children:
+                iteration_status = iteration.info.status
+                print(iteration.info.run_id + ": " + iteration_status)
+                assert iteration_status in ["FINISHED", "CANCELED", "KILLED"]
+                if iteration_status == "FINISHED":
+                    metrics = iteration.data.metrics
+                    print(metric_name + " = " + str(metrics[metric_name]))
+                    assert metrics[metric_name] >= absolute_minimum_score
+                    assert metrics[metric_name] <= absolute_maximum_score
+                    if (
+                        metrics[metric_name] < minimum_median_score
+                        or metrics[metric_name] > maximum_median_score
+                    ):
+                        badScoreCount += 1
+                    else:
+                        goodScoreCount += 1
+            assert badScoreCount < goodScoreCount
+    print("check_experiment_result complete")
+
+
+def getNotebookRuns(runs, file_name, folder):
+    root_run_ids = set(
+        run.data.tags["mlflow.rootRunId"]
+        for run in runs
+        if run.data.tags["mlflow.rootRunId"] + "_setup" == run.info.run_id
+    )
+    full_name = os.path.join(folder, file_name)
+    notebook_run_ids = []
+
+    with open(full_name, "r") as notebook_file:
+        notebook_output = notebook_file.read()
+
+        return [runid for runid in root_run_ids if runid in notebook_output]
+
+
+def getChildRuns(runs, root_run_id):
+    return [
+        run
+        for run in runs
+        if run.data.tags["mlflow.rootRunId"] == root_run_id
+        and run.info.run_id.replace(
+            run.data.tags["mlflow.rootRunId"] + "_", ""
+        ).isdigit()
+    ]
+
+
+checkExperimentResult(
+    inputArgs.experiment_name,
+    inputArgs.file_name,
+    inputArgs.folder,
+    inputArgs.metric_name,
+    inputArgs.expected_num_iteration or 1000,
+    inputArgs.minimum_median_score,
+    inputArgs.absolute_minimum_score or 0.0,
+    inputArgs.maximum_median_score or 1.0,
+    inputArgs.absolute_maximum_score or 1.0,
+    inputArgs.expected_run_count or 1,
+    inputArgs.vision_train_run,
+)
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-classification-task-bankmarketing-automl-classification-task-bankmarketing.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-classification-task-bankmarketing-automl-classification-task-bankmarketing.yml
index ed2f54e1ce..643bd45e8a 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-classification-task-bankmarketing-automl-classification-task-bankmarketing.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-classification-task-bankmarketing-automl-classification-task-bankmarketing.yml
@@ -71,14 +71,14 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-classification-task-bankmarketing
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name automl-classification-task-bankmarketing.output.ipynb \
                 --folder . \
                 --check warning \
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-classification-task-bankmarketing
     - name: check v2 experiment result
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_v2_experiment_result.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_v2_experiment_result.py \
                 --file_name automl-classification-task-bankmarketing.output.ipynb \
                 --folder . \
                 --experiment_name dpv2-classifier-experiment \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-github-dau-auto-ml-forecasting-github-dau.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-github-dau-auto-ml-forecasting-github-dau.yml
index 28645a59fb..6a68dcdbc6 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-github-dau-auto-ml-forecasting-github-dau.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-github-dau-auto-ml-forecasting-github-dau.yml
@@ -73,7 +73,7 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-forecasting-github-dau
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name auto-ml-forecasting-github-dau.output.ipynb \
                 --folder . \
                 --check warning \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-orange-juice-sales-automl-forecasting-orange-juice-sales-mlflow.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-orange-juice-sales-automl-forecasting-orange-juice-sales-mlflow.yml
index 33fa906c7f..11efcafa06 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-orange-juice-sales-automl-forecasting-orange-juice-sales-mlflow.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-orange-juice-sales-automl-forecasting-orange-juice-sales-mlflow.yml
@@ -73,14 +73,14 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-forecasting-orange-juice-sales
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name automl-forecasting-orange-juice-sales-mlflow.output.ipynb \
                 --folder . \
                 --check warning \
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-forecasting-orange-juice-sales
     - name: check v2 experiment result
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_v2_experiment_result.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_v2_experiment_result.py \
                 --file_name automl-forecasting-orange-juice-sales-mlflow.output.ipynb \
                 --folder . \
                 --experiment_name dpv2-forecasting-experiment \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-task-bike-share-auto-ml-forecasting-bike-share.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-task-bike-share-auto-ml-forecasting-bike-share.yml
index 059e75f8ce..04acdeb0d1 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-task-bike-share-auto-ml-forecasting-bike-share.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-task-bike-share-auto-ml-forecasting-bike-share.yml
@@ -73,14 +73,14 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-bike-share
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name auto-ml-forecasting-bike-share.output.ipynb \
                 --folder . \
                 --check warning \
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-bike-share
     - name: check v2 experiment result
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_v2_experiment_result.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_v2_experiment_result.py \
                 --file_name auto-ml-forecasting-bike-share.output.ipynb \
                 --folder . \
                 --experiment_name dpv2-bike-test \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-task-energy-demand-automl-forecasting-task-energy-demand-advanced.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-task-energy-demand-automl-forecasting-task-energy-demand-advanced.yml
index a4b2d2785d..bd198f724f 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-task-energy-demand-automl-forecasting-task-energy-demand-advanced.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-task-energy-demand-automl-forecasting-task-energy-demand-advanced.yml
@@ -71,14 +71,14 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-energy-demand
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name automl-forecasting-task-energy-demand-advanced.output.ipynb \
                 --folder . \
                 --check warning stderr \
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-energy-demand
     - name: check v2 experiment result
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_v2_experiment_result.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_v2_experiment_result.py \
                 --file_name automl-forecasting-task-energy-demand-advanced.output.ipynb \
                 --folder . \
                 --experiment_name dpv2-forecasting-experiment \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-classification-multiclass-task-sentiment-analysis-automl-nlp-multiclass-sentiment.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-classification-multiclass-task-sentiment-analysis-automl-nlp-multiclass-sentiment.yml
index 58d9b68a8b..5d92eb55cd 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-classification-multiclass-task-sentiment-analysis-automl-nlp-multiclass-sentiment.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-classification-multiclass-task-sentiment-analysis-automl-nlp-multiclass-sentiment.yml
@@ -71,7 +71,7 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-nlp-text-classification-multiclass-task-sentiment-analysis
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name automl-nlp-multiclass-sentiment.output.ipynb \
                 --folder . \
                 --check warning stderr \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-classification-multilabel-task-paper-categorization-automl-nlp-multilabel-paper-cat.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-classification-multilabel-task-paper-categorization-automl-nlp-multilabel-paper-cat.yml
index 5567cfe66e..3892a00183 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-classification-multilabel-task-paper-categorization-automl-nlp-multilabel-paper-cat.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-classification-multilabel-task-paper-categorization-automl-nlp-multilabel-paper-cat.yml
@@ -71,7 +71,7 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-nlp-text-classification-multilabel-task-paper-categorization
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name automl-nlp-multilabel-paper-cat.output.ipynb \
                 --folder . \
                 --check warning stderr \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-named-entity-recognition-task-automl-nlp-text-ner-task.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-named-entity-recognition-task-automl-nlp-text-ner-task.yml
index afdd5ca1a6..210c28068d 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-named-entity-recognition-task-automl-nlp-text-ner-task.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-named-entity-recognition-task-automl-nlp-text-ner-task.yml
@@ -71,7 +71,7 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-nlp-text-named-entity-recognition-task
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name automl-nlp-text-ner-task.output.ipynb \
                 --folder . \
                 --check warning stderr \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-named-entity-recognition-task-distributed-sweeping-automl-nlp-text-ner-task-distributed-with-sweeping.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-named-entity-recognition-task-distributed-sweeping-automl-nlp-text-ner-task-distributed-with-sweeping.yml
index f6d6b52d1d..833e36acc4 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-named-entity-recognition-task-distributed-sweeping-automl-nlp-text-ner-task-distributed-with-sweeping.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-nlp-text-named-entity-recognition-task-distributed-sweeping-automl-nlp-text-ner-task-distributed-with-sweeping.yml
@@ -71,7 +71,7 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-nlp-text-named-entity-recognition-task-distributed-sweeping
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name automl-nlp-text-ner-task-distributed-with-sweeping.output.ipynb \
                 --folder . \
                 --check warning stderr \
diff --git a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-regression-task-hardware-performance-automl-regression-task-hardware-performance.yml b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-regression-task-hardware-performance-automl-regression-task-hardware-performance.yml
index 651975a7fa..581e02c206 100644
--- a/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-regression-task-hardware-performance-automl-regression-task-hardware-performance.yml
+++ b/.github/workflows/sdk-jobs-automl-standalone-jobs-automl-regression-task-hardware-performance-automl-regression-task-hardware-performance.yml
@@ -71,14 +71,14 @@ jobs:
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-regression-task-hardware-performance
     - name: check notebook output
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_notebook_output.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_notebook_output.py \
                 --file_name automl-regression-task-hardware-performance.output.ipynb \
                 --folder . \
                 --check warning stderr \
       working-directory: sdk/python/jobs/automl-standalone-jobs/automl-regression-task-hardware-performance
     - name: check v2 experiment result
       run: |
-         python ${{ github.workspace }}/v1/scripts/validation/check_v2_experiment_result.py \
+         python ${{ github.workspace }}/.github/test/scripts/check_v2_experiment_result.py \
                 --file_name automl-regression-task-hardware-performance.output.ipynb \
                 --folder . \
                 --experiment_name dpv2-regression-experiment \
diff --git a/sdk/python/readme.py b/sdk/python/readme.py
index b98b7f4b41..70f0e7cac1 100644
--- a/sdk/python/readme.py
+++ b/sdk/python/readme.py
@@ -167,7 +167,7 @@ def get_validation_check_yml(notebook_folder, notebook_name, validation):
     check_yml = f"""
     - name: {validation_name}
       run: |
-         python {github_workspace}/v1/scripts/validation/{validation_file_name}.py \\
+         python {github_workspace}/.github/test/scripts/{validation_file_name}.py \\
                 --file_name {notebook_output_file} \\
                 --folder . \\"""