IBM Watson Data Scientist v1 認定 C1000-154 試験問題:

1. The first step in performing exploratory data analysis (EDA) typically involves:

A) Connecting to as many data sources as possible
B) Choosing a color palette for data visualization
C) Selecting a random sample of data to analyze
D) Determining the hypothesis for the analysis

2. How does the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology begin its process model?

A) Model Building
B) Evaluation
C) Data Preparation
D) Business Understanding

3. To add data assets from the catalog to a project in Cloud Pak for Data, which step is essential?

A) Assessing the compatibility of data formats
B) Selecting random data sets for variety
C) Maximizing the volume of data regardless of relevance
D) Browsing data assets based solely on their names

4. When helping businesses articulate and define problems, what is an essential first step?

A) Establishing a clear problem statement
B) Identifying potential data sources
C) Defining key performance indicators (KPIs)
D) Selecting the analytical techniques

5. In IBM Garage Methodology, the 'Minimum Viable Product' (MVP) concept is crucial for:

A) Testing hypotheses with the smallest investment of time and resources
B) Maximizing the budget before the product launch
C) Waiting for all possible features to be developed before release
D) Extending the timeline of the project indefinitely

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