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IBM C1000-154 Exam Overview:
| Certification Vendor: | IBM |
|---|---|
| Exam Name: | IBM Watson Data Scientist v1 |
| Exam Number: | C1000-154 |
| Exam Format: | Multiple choice, Scenario-based questions |
| Available Languages: | English |
| Related Certifications: | IBM Data Science Professional IBM AI Engineering |
| Certificate Validity Period: | 3 years |
| Exam Duration: | 90-120 |
| Recommended Training: | IBM Data Science Learning Path |
| Exam Registration: | IBM Certification Portal |
| Sample Questions: | IBM C1000-154 Sample Questions |
| Exam Way: | Online proctored exam via IBM certification platform or authorized testing provider |
| Pre Condition: | No strict prerequisites; recommended familiarity with Python and basic data science concepts |
| Official Syllabus URL: | https://www.ibm.com/training/certification |
IBM C1000-154 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| IBM Watson Tools and Platform | - IBM Watson Studio usage - Model development and deployment |
| Data Preparation and Analysis | - Data cleaning and preprocessing - Exploratory data analysis - Feature engineering basics |
| Data Visualization and Communication | - Communicating insights to stakeholders - Visualization techniques |
| Machine Learning Methods | - Supervised learning - Model evaluation and validation - Unsupervised learning |
| Data Science Fundamentals | - Data science lifecycle - Types of data and data sources |
IBM Watson Data Scientist v1 Sample Questions:
Question #1
Which of the following best exemplifies the use of the CRISP-DM methodology in a business context?
- A. A team iterating between different stages as needed based on project feedback
- B. A company following a strict top-down approach for all decisions
- C. A business starting with data collection before understanding the problem
- D. A project manager focusing exclusively on deployment
Answer: A
Question #2
In Cognos Analytics, which two features distinguish stories from dashboards?
- A. Stories are text-based and do not contain visualizations.
- B. Stories automatically load different filters for different users.
- C. Stories can be embedded in websites or documents.
- D. Stories convey a conclusion.
- E. Stories provide a narrative over time.
Answer: D,E
Question #3
What is a key disadvantage of using Grid Search for hyperparameter tuning?
- A. It is unable to handle discrete parameters
- B. It requires no prior knowledge of the hyperparameters
- C. It can be computationally expensive and time-consuming due to its exhaustive nature
- D. It is too quick and may miss out on evaluating some hyperparameters
Answer: C
Question #4
What is the primary purpose of partitioning data into training and test sets?
- A. To ensure that the model gets exposed to all possible data scenarios during training
- B. To maximize the accuracy of the model by using all data for training
- C. To evaluate the model's performance on unseen data
- D. To increase the computational efficiency of model training
Answer: C
Question #5
How does the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology begin its process model?
- A. Evaluation
- B. Data Preparation
- C. Business Understanding
- D. Model Building
Answer: C
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