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IBM Cloud Pak for Data v4.x is a comprehensive data and AI platform that provides a range of tools and services to help organizations manage their data and gain insights into their business operations. This platform is designed to help organizations accelerate their AI and machine learning initiatives, automate data management processes, and improve collaboration and data governance. The IBM C1000-136 certification exam covers a wide range of topics related to IBM Cloud Pak for Data v4.x, including architecture, installation and configuration, data management, security, and monitoring.
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IBM C1000-136: IBM Cloud Pak for Data v4.x Solution Architecture exam is a certification exam that tests the candidate's knowledge and skills in the use of IBM Cloud Pak for Data v4.x. C1000-136 exam covers several topics such as the architecture, design, and implementation of IBM Cloud Pak for Data v4.x solutions. To prepare for the exam, candidates must have a deep understanding of IBM Cloud Pak for Data v4.x and can use online resources, training materials, and practice exams to prepare. Passing the exam will result in an IBM Cloud Pak for Data v4.x Solution Architecture certification from IBM.
Reference: https://www.ibm.com/training/certification/C0004601
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IBM C1000-136 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Analytics | 17% | - Map business opportunities into an Analytics use case - Capabilities of AI for financial operations in Cloud Pak for Data - Difference between Descriptive, Prescriptive, Predictive, Diagnostic, and Cognitive Analytics - Capabilities of business intelligence in Cloud Pak for Data |
| Cloud Pak for Data Architecture | 21% | - Secure the solution and client data - Understand Cloud Pak for Data reliability options - Understand Cloud Pak for Data reference architecture - Understand the underlying infrastructure and installation - Understand sizing and deployment options |
| Data Governance | 22% | - Leverage the platform to understand data flow and usage - Capabilities of a data fabric topology - Use smart ingestion for auto cataloging - Map business opportunities into a data governance use case - Explain the concepts of Knowledge Accelerators - Explain the use of Guardium in auditing and monitoring data - Define the Governance structure - Understand how workflow is used in Cloud Pak for Data |
| Build Data Science Algorithms | 14% | - Map business opportunities into a Data Science use case - Differences between traditional programming and machine learning - Collect, explore, and prepare data for ML/AI algorithms - Process and tools in Cloud Pak for Data to build, deploy, and monitor ML/AI algorithms - Build and deploy ML/AI algorithms in Cloud Pak for Data |
| Machine Learning Operations | 16% | - Manage risk and regulatory compliance using OpenPages - Monitor deployed models inside Cloud Pak for Data - Key considerations when selecting a platform for model deployment - Monitor machine learning models running on an external platform - Workflow of deploying and monitoring models |
| Integration, Implementation, Deployment, and Scaling | 10% | - Develop a strategy to monitor the Data and AI platform - Integrate Business Applications using Cloud Pak for Data - Accelerate the solution using Industry Accelerators and External Data sets - Develop process to take a Data and AI solution from inception to production |
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