C1000-154問題集、IBM実際の試験問題

質問 1

In the context of deployment environments, understanding resources is crucial.
What does this typically involve?

A. Selecting the programming language with the least number of keywords

B. Determining the computational power and memory requirements for the deployed solution

C. Focusing exclusively on the cost of storage

D. Choosing the most aesthetically pleasing user interface

正解: B

質問 2

Which of the following is NOT a direct benefit of connecting to data sources using Cloud Pak for Data?

A. Facilitating secure and scalable data connectivity

B. Streamlining the integration of diverse data sources

C. Automatically generating insights without data analysis

D. Enhancing collaboration across data science and IT teams

正解: C

質問 3

Which two packages can be used to customize the software configuration of a Jupyter notebook environment in Cloud Pak for Data?

A. vim

B. conda

C. pip

D. bash

E. sudo

正解: B,C

質問 4

Assessing the feasibility of a solution(s) often requires evaluating:

A. Preferred communication channels of the project manager

B. Technical feasibility, cost, and time constraints

C. The color scheme of the user interface

D. Market competition only

正解: B

質問 5

Which of the following is a common issue identified during the preprocessing of data?

A. Overly detailed documentation

B. Excessively large file names

C. Aesthetically unpleasing charts

D. Presence of missing values

正解: D

質問 6

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

A. Business Understanding

B. Model Building

C. Evaluation

D. Data Preparation

正解: A

質問 7

What is the primary purpose of partitioning data into training and test sets?

A. To evaluate the model's performance on unseen data

B. To maximize the accuracy of the model by using all data for training

C. To increase the computational efficiency of model training

D. To ensure that the model gets exposed to all possible data scenarios during training

正解: A

質問 8

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

A. Maximizing the budget before the product launch

B. Extending the timeline of the project indefinitely

C. Waiting for all possible features to be developed before release

D. Testing hypotheses with the smallest investment of time and resources

正解: D

質問 9

When would you use AutoAI to select algorithms for your model?

A. When the model requirements are extremely specific and no standard algorithm fits.

B. When you have a deep understanding of all available algorithms and want to manually tune hyperparameters.

C. When you want to automatically explore multiple algorithms and hyperparameters to find the best model.

D. Only when working with small datasets due to processing limitations.

正解: C

IBM Watson Data Scientist v1 - C1000-154 模擬練習