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IBM C1000-154 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Preparation and Analysis | - Feature engineering basics - Exploratory data analysis - Data cleaning and preprocessing |
| IBM Watson Tools and Platform | - IBM Watson Studio usage - Model development and deployment |
| Data Science Fundamentals | - Data science lifecycle - Types of data and data sources |
| Data Visualization and Communication | - Visualization techniques - Communicating insights to stakeholders |
| Machine Learning Methods | - Unsupervised learning - Supervised learning - Model evaluation and validation |
IBM Watson Data Scientist v1 Sample Questions:
F1-score is particularly useful when:
- A. The data is completely balanced.
- B. The dataset size is extremely large.
- C. Only the model's accuracy matters.
- D. You need a balance between precision and recall.
Correct Answer: D 🗳️
Which statistical method reduces the number of attributes by lumping highly correlated attributes together?
- A. Synthetic Minority Over-sampling Technique (SMOTE)
- B. Principal Component Analysis (PCA)
- C. Binning
- D. Long Short Term Memory Network (LSTM)
Correct Answer: B 🗳️
Cloud Pak for Data's integration with Spark allows users to:
- A. Leverage distributed computing for processing large datasets efficiently
- B. Use Spark exclusively for data visualization purposes
- C. Perform complex computations on small datasets only
- D. Avoid using any form of data processing or analysis
Correct Answer: A 🗳️
Which hyperparameter is NOT commonly adjusted in a deep learning model?
- A. Activation function
- B. Learning rate
- C. Number of layers
- D. The color of the model's output
Correct Answer: D 🗳️
To add data assets from the catalog to a project in Cloud Pak for Data, which step is essential?
- A. Browsing data assets based solely on their names
- B. Assessing the compatibility of data formats
- C. Selecting random data sets for variety
- D. Maximizing the volume of data regardless of relevance
Correct Answer: B 🗳️
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