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IBM C1000-144 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Evaluate Business Problem Including Ethical Implications | 21% | - Business Problem Evaluation
- 1. Understand ethical challenges in the business problem
- 2. Perform AI design thinking
- 3. Understand available data
- 4. Assess progress on the AI Ladder
- 5. Understand business requirements
|
| IBM Watson Studio and AI Tools | 18% | - IBM AI Platform Usage
- 1. Collaborate within data science environments
- 2. Work with IBM AI tools and services
- 3. Use IBM Watson Studio
- 4. Manage projects and assets
|
| Exploratory Data Analysis Including Data Preparation | 18% | - Data Understanding and Preparation
- 1. Handle missing values and outliers
- 2. Explore and profile data
- 3. Prepare and clean data
- 4. Perform feature engineering
- 5. Visualize and summarize data
|
| Model Deployment and Monitoring | 20% | - Operationalization
- 1. Deploy machine learning models
- 2. Manage model lifecycle
- 3. Monitor model performance
- 4. Implement enterprise AI workflows
|
| Model Selection and Development | 23% | - Machine Learning Modeling
- 1. Interpret model results
- 2. Optimize model parameters
- 3. Train machine learning models
- 4. Evaluate model performance
- 5. Select appropriate machine learning algorithms
|