Exam Code: C1000-177
Exam Name: Foundations of Data Science using IBM watsonx
Updated: Sep 16, 2026
Q & A: 0 Questions and Answers
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| Section | Weight | Objectives |
|---|---|---|
| Perform Exploratory Data Analysis | 21% | - Assess data characteristics to guide future processing - Visually examine the data for data understanding - Deselect features that have minimal predictive value - Conduct statistical analysis of data - Visualize data to identify patterns/trends |
| Development Tools and Techniques | 13% | - Select the appropriate environment and libraries - Assess which modeling and statistical techniques are best suited |
| Evaluate the Business Problem | 16% | - Translate business objectives into Data Science/ML/AI solutions - Formulate the hypothesis to be tested - Identify appropriate tools for analysis |
| Pre-Processing and Feature Engineering | 33% | - Normalize data - Integrate data from different sources and formats - Select relevant features - Identify the best categorical data encoding techniques - Handle data anomalies and missing values - Transform features - Mitigate imbalanced data |
| Model Selection, Training, Evaluation, and Presentation | 17% | - Split the data to support model evaluation - Choose appropriate model metrics to assess model performance - Identify adequate machine learning model |
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