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IBM C1000-154 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Watson AI Services and Deployment | 10-15% | - Watson Discovery overview - Deploying models as REST APIs - Watson Assistant integration - Monitoring deployed models |
| Topic 2: Data Science and Watson Fundamentals | 20-25% | - Data collection, preparation, and exploration - IBM Watson ecosystem and components - Data science methodology and CRISP-DM framework |
| Topic 3: Machine Learning and Model Development | 20-25% | - Model deployment and monitoring - Feature engineering and selection - Model training, evaluation, and optimization - Supervised and unsupervised learning concepts |
| Topic 4: Watson Studio and Watson Knowledge Catalog | 20-25% | - Data asset management - AutoAI and automatic model building - Project management and collaboration - Data governance and cataloging |
| Topic 5: Data Visualization and Storytelling | 15-20% | - Visualization best practices - Communicating findings to stakeholders - Interactive dashboards and reports |
IBM Watson Data Scientist v1 Sample Questions:
A virtual assistant has been developed and deployed based on the Watson Assistant service. The assistant will support customers by answering FAQs (Frequent Answered Questions).
Which metric is a good indicator of the performance of the virtual assistant?
- A. The F1 score of predicted intents in the Analytics tab
- B. Measure escalated calls using A/B testing
- C. The Area Under the Curve (AUC)
- D. The Root Mean Squared Error (RMSE) of words
Correct Answer: B 🗳️
In IBM Garage Methodology, the 'Minimum Viable Product' (MVP) concept is crucial for:
- A. Maximizing the budget before the product launch
- B. Testing hypotheses with the smallest investment of time and resources
- C. Extending the timeline of the project indefinitely
- D. Waiting for all possible features to be developed before release
Correct Answer: B 🗳️
Given the Confusion matrix below, which is the formula for specificity?
- A. TP/(FN + TP)
- B. TN/(TN + FP)
- C. TP/(FP + TP)
- D. (TP + TN)/(FN + FP + TN + TP)
Correct Answer: B 🗳️
Which Python library is commonly used for data manipulation and analysis, and is available in Cloud Pak for Data?
- A. PyTorch
- B. Keras
- C. Pandas
- D. TensorFlow
Correct Answer: C 🗳️
In the context of assessing data quality in Watson Knowledge Catalog (WKC) and Cloud Pak for Data (CPD), what is a primary focus?
- A. Analyzing completeness, consistency, and accuracy of data
- B. Increasing the volume of data collected
- C. Focusing on the data's color scheme
- D. Enhancing the graphical user interface
Correct Answer: A 🗳️
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