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IBM C1000-154 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Science Fundamentals | - Data science lifecycle - Types of data and data sources |
| IBM Watson Tools and Platform | - IBM Watson Studio usage - Model development and deployment |
| Machine Learning Methods | - Supervised learning - Model evaluation and validation - Unsupervised learning |
| Data Visualization and Communication | - Visualization techniques - Communicating insights to stakeholders |
| Data Preparation and Analysis | - Feature engineering basics - Data cleaning and preprocessing - Exploratory data analysis |
IBM Watson Data Scientist v1 Sample Questions:
1. Given the Confusion matrix below, which is the formula for specificity?
A) TP/(FP + TP)
B) TN/(TN + FP)
C) TP/(FN + TP)
D) (TP + TN)/(FN + FP + TN + TP)
2. Assessing the feasibility of a solution(s) often requires evaluating:
A) Market competition only
B) The color scheme of the user interface
C) Preferred communication channels of the project manager
D) Technical feasibility, cost, and time constraints
3. Which of the following is a critical first step in understanding a business problem for data science projects?
A) Choosing the visualization tools
B) Defining the project scope
C) Selecting the machine learning algorithm
D) Deploying the model
4. What is a critical consideration when selecting the right model class for a given problem?
A) The model's ability to produce results quickly, regardless of accuracy.
B) The availability of high-performance computing resources.
C) The nature of the problem (e.g., classification, regression) and the characteristics of the data.
D) The theoretical complexity of the model, with more complex models always being preferred.
5. Which Python library is commonly used for data manipulation and analysis, and is available in Cloud Pak for Data?
A) TensorFlow
B) Keras
C) PyTorch
D) Pandas
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: D |
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