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IBM C1000-154 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Evaluate the Model | 15% | - Identify bias and overfitting - Validate model generalizability - Assess classification/regression metrics |
| Topic 2: Visualization and Storytelling | 5% | - Communicate results to stakeholders - Create effective visualizations |
| Topic 3: Prepare the Data | 18% | - Handle missing values and outliers - Clean, transform, and normalize datasets - Use Watson tools for data preparation - Feature engineering and selection |
| Topic 4: Build the Model | 20% | - Perform hyperparameter tuning - Train models using Watson AutoAI and SPSS - Select appropriate ML algorithms - Compare and select best performing models |
| Topic 5: Collect and Explore the Data | 15% | - Perform descriptive statistics and exploratory analysis - Identify and access data sources in Watson Studio - Detect patterns, outliers, and correlations |
| Topic 6: Deploy the Solution | 10% | - Deploy models as APIs in Watson - Ensure scalability and reliability - Monitor model performance post-deployment |
| Topic 7: Governance and Compliance | 5% | - Data security and privacy regulations - Model governance and lineage tracking |
| Topic 8: Understand the Business Problem | 12% | - Translate business requirements into data science objectives - Apply data science methodologies (CRISP-DM) - Define success metrics and constraints |
IBM Watson Data Scientist v1 Sample Questions:
1. When deploying models in Watson Machine Learning, what is essential for ensuring the models perform as expected in production?
A) Using the highest number of resources for every model
B) Limiting access to the model to a few select users
C) Deployment without any security measures
D) Continuous monitoring and evaluation of model performance
2. Given the Confusion matrix below, which is the formula for specificity?
A) TP/(FN + TP)
B) TP/(FP + TP)
C) TN/(TN + FP)
D) (TP + TN)/(FN + FP + TN + TP)
3. An E-retailer uses several important data sources, including web logs which contain all of the information on how customers navigate the web site. There are non-informative entries in the web logs that need to be removed.
During which phase should these non-informative entries be removed in the CRISP-DM model?
A) Modeling
B) Data Understanding
C) Data Preparation
D) Business Understanding
4. When implementing cross-validation, which of the following is NOT a common approach?
A) Leave-One-Out Cross-Validation (LOOCV)
B) K-Fold Cross-Validation
C) Stratified K-Fold Cross-Validation for imbalanced datasets
D) Using the entire dataset as both the training and the test set in each iteration
5. When helping businesses articulate and define problems, what is an essential first step?
A) Selecting the analytical techniques
B) Establishing a clear problem statement
C) Identifying potential data sources
D) Defining key performance indicators (KPIs)
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: B |
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