text: # See also examples/example_track/example_meta.py for a longer, commented example
  track = dict(
      author_username='dansbecker',
      course_name='Introduction to Machine Learning',
      course_url='https://www.kaggle.com/learn/intro-to-machine-learning'
  )
  
  lessons = [ {'topic': topic_name} for topic_name in
                      ['How Models Work',
                      'Basic Data Exploration',
                      'Your First Machine Learning Model',
                      'Model Validation',
                      'Underfitting and Overfitting',
                      'Random Forests',
                      'Machine Learning Competitions',
                      'Classification']
              ]
  
  notebooks = [
      dict(
          filename='tut1.ipynb',
          lesson_idx=0,
          type='tutorial',
          ),
      dict(
          filename='tut2.ipynb',
          lesson_idx=1,
          type='tutorial',
          ),
      dict(
          filename='ex2.ipynb',
          lesson_idx=1,
          type='exercise',
          scriptid=1258954
      ),
      dict(
          filename='tut3.ipynb',
          lesson_idx=2,
          type='tutorial'
      ),
      dict(
          filename='ex3.ipynb',
          lesson_idx=2,
          type='exercise',
          scriptid=400771
      ),
      dict(
          filename='tut4.ipynb',
          lesson_idx=3,
          type='tutorial'
      ),
      dict(
          filename='ex4.ipynb',
          lesson_idx=3,
          type='exercise',
          scriptid=1259097
      ),
      dict(
          filename='tut5.ipynb',
          lesson_idx=4,
          type='tutorial'
          ),
      dict(
          filename='ex5.ipynb',
          lesson_idx=4,
          type='exercise',
          scriptid=1259126
          ),
      dict(filename='tut6.ipynb',
          lesson_idx=5,
          type='tutorial'
          ),
      dict(
          filename='ex6.ipynb',
          lesson_idx=5,
          type='exercise',
          scriptid=1259186
          ),
      dict(
          filename='ex7.ipynb',
          lesson_idx=6,
          type='exercise',
          scriptid=1259198
          ),
      dict(filename='tut8.ipynb',
          lesson_idx=7,
          type='tutorial'
          ),
      dict(filename='ex8.ipynb',
          lesson_idx=7,
          type='exercise',
          scriptid=3685412
          ),
  ]
  
  for nb in notebooks:
      nb['competition_sources'] = ["home-data-for-ml-course"]
      nb['dataset_sources'] = ["dansbecker/melbourne-housing-snapshot",
                               "iabhishekofficial/mobile-price-classification",
                               "pavanraj159/predicting-a-pulsar-star"]
  
      # ex7 is special case with only comp dataset, to allow submission from kernel
      if nb['filename'] == 'ex7.ipynb':
          nb['dataset_sources'] = []
  