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IBM Watson Data Scientist v1 Sample Questions:

1. When deploying models in Watson Machine Learning, what is essential for ensuring the models perform as expected in production?

A) Limiting access to the model to a few select users
B) Deployment without any security measures
C) Continuous monitoring and evaluation of model performance
D) Using the highest number of resources for every model

2. A virtual assistant has been developed and deployed based on the Watson Assistant service. The assistant will support customers by answering FAQs (Frequent Answered Questions).
Which metric is a good indicator of the performance of the virtual assistant?

A) The Area Under the Curve (AUC)
B) The Root Mean Squared Error (RMSE) of words
C) The F1 score of predicted intents in the Analytics tab
D) Measure escalated calls using A/B testing

3. Selecting the right model for a data science project depends on:

A) The size of the dataset only
B) The preference of the data scientist
C) The type of data and the problem to be solved
D) The project's budget only

4. When determining upskill requirements for a team working on a solution, it is important to consider:

A) The budget allocation for the project
B) The existing skill level of the team and the skills required for the project
C) The geographical location of the team members
D) The preferred programming languages of the team

5. Automating data processing and model deployment with jobs in Watson Studio helps to:

A) Reduce the scalability of deployed solutions
B) Increase the need for manual intervention in the model lifecycle
C) Limit the ability to update models based on new data
D) Enhance the reproducibility and efficiency of model deployments

Solutions: