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IBM C1000-154 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Watson AI Services and Deployment | 10-15% | - Watson Assistant integration - Monitoring deployed models - Deploying models as REST APIs - Watson Discovery overview |
| Topic 2: Data Visualization and Storytelling | 15-20% | - Visualization best practices - Communicating findings to stakeholders - Interactive dashboards and reports |
| Topic 3: Machine Learning and Model Development | 20-25% | - Model training, evaluation, and optimization - Feature engineering and selection - Model deployment and monitoring - Supervised and unsupervised learning concepts |
| Topic 4: Watson Studio and Watson Knowledge Catalog | 20-25% | - AutoAI and automatic model building - Data asset management - Data governance and cataloging - Project management and collaboration |
| Topic 5: Data Science and Watson Fundamentals | 20-25% | - Data collection, preparation, and exploration - IBM Watson ecosystem and components - Data science methodology and CRISP-DM framework |
IBM Watson Data Scientist v1 Sample Questions:
1. In the deployment phase, why is it important to know the different data sources available in Cloud Pak for Data?
A) Because only one type of data source can be used in any deployment
B) To limit the deployment to only use local file storage
C) To ensure that all data sources are manually processed
D) To effectively integrate and manage data from various sources for analysis and model training
2. The first step in performing exploratory data analysis (EDA) typically involves:
A) Selecting a random sample of data to analyze
B) Connecting to as many data sources as possible
C) Choosing a color palette for data visualization
D) Determining the hypothesis for the analysis
3. When managing data with Cloud Pak for Data Services, what is a common task?
A) Using the same data management approach for all types of data, regardless of size or format
B) Avoiding the automation of data processing tasks
C) Ignoring data security and compliance requirements
D) Reading data from and writing data to Watson Studio
4. Which two graph types are used in EDA to show the relationship between two or more quantitative variables?
A) Stem-and-leaf plot
B) Heat map
C) Scatter plot
D) Box plot
E) Histogram
5. Which method is NOT traditionally used for collecting data?
A) Using SQL to fetch data from a data warehouse
B) Scraping data from a webpage
C) Predicting future trends with machine learning models
D) Using Python APIs for external data
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: B,C | Question # 5 Answer: C |
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