Just run from the folder it's in, and finished environment

azuremlpythonsdk-v2/data_tabular.py

@@ -7,7 +7,7 @@ from azure.ai.ml.entities import Data
 from ml_client import create_or_load_ml_client
 
 name_dataset = "diabetes-dataset"
-data_folder = "./azuremlpythonsdk-v2/data/diabetes.csv"
+data_folder = "./data/diabetes.csv"
 
 
 def create_tabular_dataset():

azuremlpythonsdk-v2/environment.py

@@ -13,12 +13,12 @@ custom_env_name = "custom-scikit-learn"
 
 def create_docker_environment():
     # 1. Create or Load a ML client
-    ml_client =  XXXXX()
+    ml_client =  create_or_load_ml_client()
 
     # 2. Create a Python environment for the experiment
-    env_docker_image = XXXXX(
+    env_docker_image = Environment(
         name=custom_env_name,
-        conda_file=os.path.join(dependencies_dir, "XXXXX"),
+        conda_file=os.path.join(dependencies_dir, "conda.yml"),
         image="mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu22.04:latest",
     )
     ml_client.environments.create_or_update(env_docker_image)