Passing the IBM C1000-059 (IBM AI Enterprise Workflow V1 Data Science Specialist)
Passing the C1000-059 (IBM AI Enterprise Workflow V1 Data Science Specialist) exam has never been easier. With the comprehensive C1000-059 Exam Prep Package, you’ll significantly increase your chances of passing on your first attempt.
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This C1000-059 Exam Prep Package has been meticulously formatted, thoroughly reviewed, and rigorously tested by a team of professional IBM trainers.
The exam package includes a PDF version of the C1000-059 exam with 62 actual questions and answers, an Interactive Xengine Test Engine Software (C1000-059 VCE).
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C1000-059 Exam Objectives & Details
Exam Objectives:
The IBM C1000-059 IBM AI Enterprise Workflow V1 Data Science Specialist exam is designed to test the candidate's proficiency in IBM AI Enterprise Workflow V1, including machine learning, deep learning, and natural language processing. The exam covers the following topics:
- Machine Learning Fundamentals
- Supervised Learning
- Unsupervised Learning
- Neural Networks and Deep Learning
- Natural Language Processing (NLP)
- IBM Watson Studio
- IBM Watson Machine Learning
- IBM Watson OpenScale
- AI Application Development
- AI Deployment and Monitoring
Exam Details:
The IBM C1000-059 IBM AI Enterprise Workflow V1 Data Science Specialist exam is a proctored exam with a time limit of 90 minutes. The exam is delivered through Pearson VUE and can be taken at a test center or online. The cost of the exam is $200 USD.
To pass the exam, the candidate must achieve a minimum score of 68%. The exam consists of 54 multiple-choice questions and is available in English, Japanese, and Portuguese.
Related Books:
IBM offers a variety of training resources and materials to help candidates prepare for the IBM C1000-059 IBM AI Enterprise Workflow V1 Data Science Specialist exam. These include online courses, self-paced learning modules, and reference books. Some recommended books that can help a candidate pass their exam are:
- Machine Learning for Dummies, IBM Limited Edition by Judith Hurwitz and Daniel Kirsch
- Practical Deep Learning for Cloud, Mobile, and Edge by Anirudh Koul, Siddha Ganju, and Meher Kasam
- Natural Language Processing with Python by Steven Bird, Ewan Klein, and Edward Loper
- Python for Data Analysis by Wes McKinney
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron
These books cover the topics that are relevant to the IBM C1000-059 IBM AI Enterprise Workflow V1 Data Science Specialist exam and can provide additional resources for the candidate to study and review the key concepts and skills required for success in the exam.
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Section Name Total Score Gained Score
Network Perimeter Protection 16 11
Incident Response 10 8
Enterprise Virtual, Cloud, and Wireless Network Protection 12 8
Application and Data Protection 13 10
Network Défense Management 10 9
Endpoint Protection 15 12
Incident D
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