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IBM C1000-154 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Governance and Compliance | 5% | - Model governance and lineage tracking - Data security and privacy regulations |
| Understand the Business Problem | 12% | - Apply data science methodologies (CRISP-DM) - Define success metrics and constraints - Translate business requirements into data science objectives |
| Evaluate the Model | 15% | - Identify bias and overfitting - Assess classification/regression metrics - Validate model generalizability |
| Deploy the Solution | 10% | - Ensure scalability and reliability - Deploy models as APIs in Watson - Monitor model performance post-deployment |
| Build the Model | 20% | - Compare and select best performing models - Select appropriate ML algorithms - Train models using Watson AutoAI and SPSS - Perform hyperparameter tuning |
| Prepare the Data | 18% | - Use Watson tools for data preparation - Handle missing values and outliers - Clean, transform, and normalize datasets - Feature engineering and selection |
| Collect and Explore the Data | 15% | - Identify and access data sources in Watson Studio - Perform descriptive statistics and exploratory analysis - Detect patterns, outliers, and correlations |
| Visualization and Storytelling | 5% | - Communicate results to stakeholders - Create effective visualizations |
IBM Watson Data Scientist v1 Sample Questions:
Question 1
Which two graph types are used in EDA to show the relationship between two or more quantitative variables?
A. Histogram
B. Box plot
C. Heat map
D. Stem-and-leaf plot
E. Scatter plot
Question 2
Which Python library is commonly used for data manipulation and analysis, and is available in Cloud Pak for Data?
A. TensorFlow
B. Keras
C. PyTorch
D. Pandas
Question 3
Understanding how to use libraries in Python within a deployment environment is essential for:
A. Ensuring that all models are developed without any external libraries
B. Deploying models that are incompatible with the deployment environment
C. Leveraging specific functionalities for data analysis, manipulation, and model building
D. Increasing the complexity and maintenance cost of the deployed solution
Question 4
In the context of deployment environments, understanding resources is crucial.
What does this typically involve?
A. Determining the computational power and memory requirements for the deployed solution
B. Selecting the programming language with the least number of keywords
C. Choosing the most aesthetically pleasing user interface
D. Focusing exclusively on the cost of storage
Question 5
Choosing the best model often involves trade-offs.
Which scenario represents such a trade-off?
A. Opting for the most complex model to ensure ease of use
B. Preferring a model with higher accuracy over one that is slightly less accurate but much more interpretable
C. Selecting a model based solely on its execution speed, without regard to accuracy
D. Choosing the model with the largest number of features, regardless of performance
Solutions:
| Question 1 Answer: C,E | Question 2 Answer: D | Question 3 Answer: C | Question 4 Answer: A | Question 5 Answer: B |




