Data Types for AI Models: 10 practice questions

Question 1 of 10

What makes a training example labeled?

1. AIt includes an explicit label or target that supplies the known answer
2. BIt groups similar inputs without using any predefined outcome
3. CIt includes a timestamp but excludes the value that should be predicted
4. DIt contains free-form media without an annotation or target value

Question 2 of 10

Which description best matches structured data?

1. AData organized in tables or fixed schemas with defined fields, rows, and columns
2. BObservations that have no labels and therefore cannot use columns
3. CFree-form text, images, audio, and video that lack the rows, columns, and fixed schema of a table
4. DVisual content that has captions but cannot be placed in a dataset

Question 3 of 10

Which feature is essential to the definition of time-series data?

1. AEvery observation is an image paired with a manually written caption and no timestamp or time period
2. BInputs are grouped by similarity without retaining their measurement time
3. CRows contain text fields but exclude identifiers and point-in-time values
4. DObservations are associated with timestamps or time periods and ordered chronologically

Question 4 of 10

What characterizes unlabeled data?

1. AThe inputs contain no supplied labels or target values, so patterns must be discovered from them
2. BThe inputs must be unstructured media and cannot use rows, columns, or fixed schemas
3. CThe inputs must include timestamps and a numeric target at regular time intervals
4. DThe inputs contain explicit targets that define the correct answer for every example

Question 5 of 10

In tabular training data, what do rows and columns commonly represent?

1. AA row represents a timestamp only, while columns contain unstructured video streams
2. BA row represents a reward action, while columns remove the need for input features
3. CA row represents a sample, while columns represent features and possibly a target label
4. DA row represents a model, while columns represent separate learning paradigms

Question 6 of 10

Which pairing correctly identifies two data modalities?

1. ABooks and emails are timestamps; photographs and diagrams are target columns
2. BBooks and emails are text data; photographs and diagrams are image data
3. CBooks and emails are tabular targets; photographs and diagrams are fixed schemas
4. DBooks and emails are image data; photographs and diagrams are time-series data

Question 7 of 10

Which statement correctly compares data properties?

1. ALabeling describes whether targets are supplied, while structure describes whether data follows a fixed schema
2. BLabeling describes rows and columns, while structure describes whether targets are correct
3. CLabeling describes chronological order, while structure describes whether an image contains a caption
4. DLabeling describes text modality, while structure describes whether observations have timestamps

Question 8 of 10

A forecasting dataset stores one row per product and day. Its columns include product ID, timestamp, sales value to predict, and weather. Which description captures all relevant properties?

1. AIt is text data and unlabeled because product IDs are language tokens rather than fields
2. BIt is tabular, structured, time-series, and labeled because it has a target sales value
3. CIt is image data and labeled because weather is a visual feature in every row
4. DIt is unstructured and unlabeled because timestamps prevent rows from having target values

Question 9 of 10

A team has product photographs paired with category captions and a separate collection of free-form customer emails with no targets. Which classification is accurate?

1. AThe photographs are labeled image data; the emails are unlabeled text and unstructured data
2. BThe photographs are time-series data; the emails are tabular because each message has words
3. CThe photographs are fixed-schema rows; the emails are labeled because their language has meaning
4. DThe photographs are unlabeled text data; the emails are labeled image and structured data

Question 10 of 10

A CSV contains rows of support tickets, fixed columns for account and region, a free-form message field, and no outcome column. The team must describe both the container and the examples. Which answer is most precise?

1. AThe CSV is unlabeled media only, the message field removes its columns, and the examples are unstructured
2. BThe CSV is tabular and structured, the message field contains text, and the examples are unlabeled
3. CThe CSV is time-series only, the message field is a target, and the examples are labeled
4. DThe CSV is unstructured image data, the message field is a timestamp, and the examples are labeled