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1. When documenting available data for an AI project, what information is crucial?

The format of the data

The volume of the data

The source of the data

All of the above

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2. How does understanding business requirements help in AI project development?

It leads to faster coding phases

It prevents scope creep and ensures that solutions are relevant

It reduces the need for project management

It allows developers to work in isolation

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3. The Bayesian optimization algorithm for hyperparameter tuning has which trait?

It can be used for both regression and clustering but cannot be used for classification.

It requires that a user provide a list of all of the values that will be tested for each hyperparameter.

It builds a machine learning model to predict which hyperparameter settings will be most effective.

If sufficient hardware is available, it can try out many different hyperparameter settings at the same time.

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4. Which of the following is a best practice for data labeling in a supervised learning project?

Labeling a random subset of data

Ensuring labels are consistent and accurate

Using automatic labeling without verification

Labeling only the features with the most variance

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5. How would you combine data from multiple types of data assets (like JSON, CSV, SQL database) into a single Pandas DataFrame?

Using the pandas.concat() function after reading each file separately

Importing all data as strings and converting formats in Python

Pandas cannot handle multiple data types in one DataFrame

Using a single read command with a universal data handler

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6. In the context of CRISP-DM, what is the purpose of the ‘Evaluation’ phase?

To assess the project budget

To determine the technical feasibility of the project

To review the process and model against business objectives

To finalize the project deliverables

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7. In k-means clustering, how is the 'k' value used?

It represents the maximum number of iterations allowed

It specifies the number of centroids or clusters to form

It is the threshold for stopping the algorithm

It determines the distance metric used for clustering

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8. Which approach would not be suitable for assessing model fairness?

Analyzing confusion matrices for different subgroups

Using the same performance metric for all models

Conducting audits on model decisions

Implementing external fairness monitoring tools

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9. Converting a neural network into the newest version of TensorFlow or another deep-learning package is what type of performance drift or software decay?

Data changes

Concept drift

Software changes

Sampling bias and selection bias changes

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10. In the context of machine learning, what does the term 'model drift' refer to?

The migration of the model from one server to another

The change in model parameters due to new updates

The change in model performance due to changes in underlying data patterns

The physical movement of the hardware running the model

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11. When configuring the environment for training a model, what is a crucial factor?

Selecting a text editor

Ensuring sufficient computational resources

Choosing the color scheme of the user interface

Setting up multiple monitors

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12. Assessing the progress of infusing AI into the organization involves evaluating what?

The number of AI-related press releases issued.

The impact of AI on improving product quality.

The variety of snacks available in meeting rooms.

The color scheme of the AI department's office.

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13. What are key considerations when training a model and optimizing hyperparameters?

Selecting the highest number of iterations regardless of overfitting

Using cross-validation to evaluate model performance

Always using the most complex model to ensure accuracy

Balancing the bias-variance tradeoff

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14. What are two reasons a data point would be treated as an outlier?

If the value is greater than mean

If the value is greater than median

If the value is greater than standard deviation

If the value is below the upper end of the bottom quartile by more then 1.5 times the interquartile range

If the value is above the lower end of the top quartile by more then 1.5 times the interquartile range

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15. When analyzing and visualizing time series data, why might you prefer a line plot over a bar chart?

Line plots are less clear than bar charts.

Line plots are better for showing the continuity of data over time.

Line plots handle large datasets more poorly than bar charts.

Line plots cannot incorporate multiple time series in one visualization.

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16. Which environment specification is least relevant when setting up a model training environment?

The type and version of the operating system

The graphics processing unit (GPU) capabilities

The brand of the computer

The available RAM and CPU power

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17. Which data points are essential to understand when analyzing available data for a business problem?

Data volume and variety

The age of the data

Sources of the data

All of the above

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18. Which SQL clause is used to filter records in a query?

SELECT

WHERE

FROM

EXTRACT

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19. You need to compare sales performance across different regions.

Which type of chart would most effectively serve this purpose?

Histogram

Box plot

Bar chart

Heatmap

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20. In the CRISP-DM process, what is primarily considered during the 'Business Understanding' phase?

Technical specifications of the required tools

Defining the business problem and initial hypotheses

Selection of algorithms for model building

Allocation of roles and responsibilities within the team

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21. What is the primary goal of clustering in unsupervised learning?

To predict the outcome for a dependent variable

To group similar instances into distinct clusters without prior labeling

To reduce the number of variables in the dataset

To classify data into predefined categories

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22. In assessing progress on the AI Ladder, which aspects should be considered? (Choose Two)

The quality and accessibility of data

The color palette of the user interface

Integration capabilities with existing systems

Branding and marketing strategies

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23. When choosing a plot to show the relationship between two ranked variables, which type of visualization is least appropriate?

Scatterplot

Heatmap

Line plot

Pie chart

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24. A Logistic Regression algorithm is used to classify images into four categories.

If each image has a 5x5 pixel dimension, what is the the number of weights required (excluding biases) for this model?

200

100

300

400

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25. How would you join the 'orders' table and the 'customers' table using the 'customer_id' field in both tables?

SELECT * FROM orders JOIN customers ON orders.customer_id = customers.customer_id;

SELECT * FROM orders LINK customers BY customer_id;

JOIN orders AND customers USING customer_id;

MERGE orders WITH customers ON customer_id;

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26. Which algorithms are considered ensemble methods? (Choose Two)

Decision Trees

Random Forest

Boosting Classifiers

Linear SVM

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27. Which type of machine learning algorithm would be best suited for predicting continuous target values?

Classification

Clustering

Regression

Recommendation engines

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28. What is one way that IBM AutoAI helps make it easier for data scientists to determine what key fields to use to join data tables?

AutoAI automatically suggests joining on fields in different tables that have matching names.

AutoAI automatically suggests joining on fields in different tables that have matching values.

AutoAI automatically suggests joining on fields in different tables when those tables have the same number of rows.

AutoAI automatically suggests joining on fields in different tables when those tables have the same number of fields.

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29. How should you assess a model that is underperforming in production?

By redesigning the user interface of the application

By recalibrating the model’s hyperparameters

By reducing the amount of input data

By increasing the frequency of model updates

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30. What is the core principle of the IBM Garage Methodology?

Utilizing high-volume data storage effectively

Maximizing remote working capabilities

Creating minimal viable products (MVPs) through iterative development

Implementing strict project management protocols

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31. Which Python library would you use to generate a heatmap to represent correlations in a dataset?

Matplotlib

Seaborn

Plotly

Bokeh

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32. Which technique is typically used to prevent overfitting in a decision tree classifier?

Increasing the depth of the tree indefinitely

Using a linear kernel instead of a polynomial kernel

Pruning the tree to remove non-significant branches

Applying PCA before training the classifier

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33. What types of training might be required when deploying an AI solution? (Choose Two)

Training on how to use the AI system for end-users

Technical training for the AI development team

Sales training for unrelated products

Leadership training on strategic decision-making

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34. What function is used in Pandas to read a CSV file into a DataFrame?

pandas.read_csv()

pandas.load_csv()

pandas.open_csv()

pandas.csv()

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35. What are effective strategies for handling missing data? (Choose Two)

Deleting all rows with any missing values

Imputing missing values using statistical methods

Using a machine learning model to predict missing values

Ignoring missing data during analysis

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36. If you are using Python for data visualization, which library would you select to create a violin plot?

Pandas

Matplotlib

Seaborn

Plotly

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37. Which approach is recommended for prioritizing business opportunities when planning an MVP?

Choosing the most straightforward implementation irrespective of impact

Assessing the potential return on investment and strategic fit

Prioritizing based on the preference of the project manager

Focusing solely on technological innovation

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38. How can you access data from an API in Python?

Using the 'api' method in the Pandas library

With the 'requests' library to make HTTP requests

By employing the 'open' function in Python's os library

Utilizing the 'import_data' module in Python

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