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IBM A1000-144 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Evaluate Business Problem Including Ethical Implications | 21% | - Understand what data is available - Understand ethical challenges in the business problem - Assess progress on the AI Ladder - Perform AI design thinking - Understand business requirements |
| Monitor Models in Production | 17% | - Determine whether unfair bias exists in the model - Assess the model - Monitor the model in production |
| Implement the Proper Model | 26% | - Implement unsupervised learning using dimensional reduction - Implement unsupervised learning using clustering - Implement supervised learning using regression - Implement supervised learning using classification |
| Exploratory Data Analysis Including Data Preparation | 18% | - Identify methods used to clean, label, and anonymize data - Visualize data - Balance and partition data |
| Refine and Deploy the Model | 18% | - Configure environment specifications for model training - Select appropriate tools - Identify operations and transformations used for feature selection and engineering - Implement model explainability - Train the model and optimize hyperparameters |
