Copyright and IP considerations in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to identify if a dataset is under copyright protection.

Prompt Engineering / GenAI

if dataset.license == [1]:
    print("Dataset is copyrighted.")

Drag options to blanks, or click blank then click option'

Aall_rights_reserved

Bpublic_domain

Ccreative_commons

Dopen_source

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'public_domain' which means no copyright.

Confusing 'open_source' with copyright restriction.

The license 'all_rights_reserved' means the dataset is copyrighted and cannot be freely used without permission.

2fill in blank

medium

Complete the code to check if a model's training data requires attribution.

Prompt Engineering / GenAI

if training_data.license == [1]:
    print("Attribution required for use.")

Drag options to blanks, or click blank then click option'

Aall_rights_reserved

Bcreative_commons_by

Cpublic_domain

Dproprietary

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'public_domain' which does not require attribution.

Confusing 'all_rights_reserved' with attribution requirement.

Creative Commons BY license requires giving credit (attribution) when using the data.

3fill in blank

hard

Fix the error in the code to avoid using copyrighted material without permission.

Prompt Engineering / GenAI

if model.uses_data_from([1]):
    raise Exception("Unauthorized use of copyrighted data")

Drag options to blanks, or click blank then click option'

Apublic_domain_sources

Blicensed_datasets

Cproprietary_datasets

Dopen_source_repos

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'public_domain_sources' which is allowed.

Confusing 'licensed_datasets' with unauthorized use.

Using proprietary datasets without permission is unauthorized and may violate copyright laws.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that filters datasets with open licenses and adds their names.

Prompt Engineering / GenAI

open_datasets = {dataset.[1]: dataset.[2] for dataset in datasets if dataset.license in ['public_domain', 'creative_commons']}

Drag options to blanks, or click blank then click option'

Aname

Blicense

Csize

Dcreator

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'size' or 'creator' instead of 'name' or 'license'.

Mixing up key and value positions.

We use 'name' as the key and 'license' as the value to list datasets with open licenses.

5fill in blank

hard

Fill all three blanks to create a comprehension that selects models trained only on datasets with allowed licenses.

Prompt Engineering / GenAI

allowed_models = [model for model in models if model.training_data.[1] in [2] and not model.training_data.[3] == 'all_rights_reserved']

Drag options to blanks, or click blank then click option'

Alicense

B['public_domain', 'creative_commons_by']

Dname

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'name' instead of 'license' to check licenses.

Not excluding 'all_rights_reserved' datasets.

We check the 'license' attribute to ensure the dataset license is allowed and exclude 'all_rights_reserved'.