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IBM C1000-059 Exam
Certification Provider: IBM
Exam Name: IBM AI Enterprise Workflow V1 Data Science Specialist
Duration: 90 Minutes
Number of questions in our database: 62
Exam Version: Apr. 18, 2024
C1000-059 Exam Official Topics:
- Topic 1: Demonstrate knowledge of scenarios for application of machine learning/ Explain the fundamental terms and concepts of design thinking
- Topic 2: Show knowledge of how to communicate technical results to business stakeholders/ Explain and calculate different types of matrix operations
- Topic 3: Demonstrate mastery preparing and cleaning unstructured text data/ Explain the different types of fundamental Data Science
- Topic 4: Demonstrate basic understanding of natural language processing/ Explain the general properties of common probability distributions
- Topic 5: Translate business opportunities into a machine learning scenario/ Show knowledge of data exploration techniques and data anomaly detection
- Topic 6: Describe the differences between traditional programming and machine learning/ Use data summarization and visualization techniques to find relevant insight
- Topic 7: Demonstrate knowledge on open source technologies for deployment of AI solutions/ Demonstrate expertise cleaning data and addressing data anomalies
- Topic 8: Demonstrate foundational knowledge of using python as a tool for building AI solutions/ Show knowledge of feature engineering and dimensionality reduction techniques
- Topic 9: Describe the key considerations when selecting a platform for AI model deployment/ Demonstrate successful application of model validation and selection methods
- Topic 10: Identify IBM technology capabilities for building, deploying, and managing AI models/ Identify use cases where artificial intelligence solutions can address business opportunities
- Topic 11: Show knowledge of the benefits of cloud computing for building and deploying AI models/ Demonstrate knowledge of requirements for model monitoring, management and maintenance
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Free IBM C1000-059 Exam Actual Questions
The questions for C1000-059 were last updated On Apr. 18, 2024
Question #1
In a hyperparameter search, whether a single model is trained or a lot of models are trained in parallel is largely determined by?
Correct Answer:
C
Question #2
A data analyst creates a term-document matrix for the following sentence: I saw a cat, a dog and another cat.
Assuming they used a binary vectorizer, what is the resulting weight for the word cat?
Correct Answer:
B
Question #3
A data scientist is exploring transaction data from a chain of stores with several locations. The data includes store number, date of sale, and purchase amount.
If the data scientist wants to compare total monthly sales between stores, which two options would be good ways to aggregate the data? (Choose two.)
Correct Answer:
B, D
Question #4
Question #5
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