Why governance builds trust in ML systems in MLOps - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a governance policy that ensures model version control.

MLOps

policy = {'model_version': [1]

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

A'v1.0'

Bmodel

Cversion

D1.0

Attempts:

3 left

💡 Hint

Common Mistakes

Using a number instead of a string for version.

The model version should be a string like 'v1.0' to clearly identify the version.

2fill in blank

medium

Complete the code to log the model training start time for audit purposes.

MLOps

import datetime
start_time = datetime.datetime.[1]()

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

Anow

Btoday

Cutcnow

Dtimestamp

Attempts:

3 left

💡 Hint

Common Mistakes

Using utcnow() which returns UTC time instead of local time.

Using datetime.datetime.now() records the current local time when training starts.

3fill in blank

hard

Fix the error in the code that checks if the model passed governance compliance.

MLOps

if compliance_status [1] True:
    print('Model approved')

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

A==

B=

Cis

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' which is assignment, not comparison.

Using 'is' checks identity with True, which is preferred for boolean checks.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that filters models with accuracy above 0.9.

MLOps

high_accuracy_models = {model: metrics[1]('accuracy') for model, metrics in model_metrics.items() if metrics['accuracy'] [2] 0.9}

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A.copy()

B>

C>=

D.get

Attempts:

3 left

💡 Hint

Common Mistakes

Using .copy() which returns a copy but does not access values.

Use .get to safely access metrics['accuracy'] and '>' to filter accuracy above 0.9.

5fill in blank

hard

Fill both blanks to create a filtered dictionary of models with version starting with 'v' and accuracy above 0.85.

MLOps

filtered_models = {model: metrics for model, metrics in all_models.items() if model[1] and metrics['accuracy'] [2] 0.85}

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

A:

B.startswith('v')

C>=

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '==' instead of .startswith() for string prefix check.

Use ':' to separate key and value, .startswith('v') to check model name, and '>=' for accuracy threshold.