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IBM C1000-136 exam is an essential certification for professionals who want to demonstrate their expertise in IBM Cloud Pak for Data v4.x solution architecture. It validates the candidate's skills and knowledge in designing, deploying, and managing IBM Cloud Pak for Data v4.x solutions. Passing C1000-136 exam can help professionals advance their careers and open up new opportunities in the fast-growing field of data and AI.
IBM C1000-136 Exam Overview:
| Certification Vendor: | IBM |
|---|---|
| Exam Name: | IBM Cloud Pak for Data v4.x Solution Architecture |
| Exam Number: | C1000-136 |
| Related Certifications: | IBM Certified Solution Architect - Cloud Pak for Data v4.x |
| Exam Price: | USD 200 (approx.) |
| Real Exam Qty: | 63 |
| Exam Format: | Multiple choice, Case studies, Multiple response |
| Available Languages: | English |
| Passing Score: | 42 out of 63 |
| Exam Duration: | 90 minutes |
| Sample Questions: | IBM C1000-136 Sample Questions |
| Exam Way: | Onsite at Pearson VUE or Online proctored exam |
| Pre Condition: | No specific prerequisite exam listed; relevant hands-on experience recommended |
| Official Syllabus URL: | https://www.ibm.com/training/certification/ibm-certified-solution-architect-cloud-pak-for-data-v4x-C0004601 |
IBM Cloud Pak for Data is a comprehensive data and analytics platform that enables businesses to harness their data and gain insights to make informed decisions. The platform is designed to support hybrid cloud environments and can be deployed on-premises or in the cloud. The IBM C1000-136 exam is an essential certification for professionals who are responsible for designing and implementing solutions that take advantage of the IBM Cloud Pak for Data platform. By passing C1000-136 exam, candidates can demonstrate their expertise in solution architecture and their ability to design and implement effective data-driven solutions.
Reference: https://www.ibm.com/training/certification/C0004601
IBM C1000-136 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Build Data Science Algorithms | 14% | - Differences between traditional programming and machine learning - Build and deploy ML/AI algorithms in Cloud Pak for Data - Map business opportunities into a Data Science use case - Process and tools in Cloud Pak for Data to build, deploy, and monitor ML/AI algorithms - Collect, explore, and prepare data for ML/AI algorithms |
| Topic 2: Analytics | 17% | - Map business opportunities into an Analytics use case - Capabilities of AI for financial operations in Cloud Pak for Data - Capabilities of business intelligence in Cloud Pak for Data - Difference between Descriptive, Prescriptive, Predictive, Diagnostic, and Cognitive Analytics |
| Topic 3: Integration, Implementation, Deployment, and Scaling | 10% | - Develop process to take a Data and AI solution from inception to production - Integrate Business Applications using Cloud Pak for Data - Accelerate the solution using Industry Accelerators and External Data sets - Develop a strategy to monitor the Data and AI platform |
| Topic 4: Data Governance | 22% | - Explain the concepts of Knowledge Accelerators - Understand how workflow is used in Cloud Pak for Data - Leverage the platform to understand data flow and usage - Use smart ingestion for auto cataloging - Capabilities of a data fabric topology - Define the Governance structure - Explain the use of Guardium in auditing and monitoring data - Map business opportunities into a data governance use case |
| Topic 5: Machine Learning Operations | 16% | - Monitor machine learning models running on an external platform - Key considerations when selecting a platform for model deployment - Monitor deployed models inside Cloud Pak for Data - Manage risk and regulatory compliance using OpenPages - Workflow of deploying and monitoring models |
| Topic 6: Cloud Pak for Data Architecture | 21% | - Understand the underlying infrastructure and installation - Secure the solution and client data - Understand Cloud Pak for Data reliability options - Understand Cloud Pak for Data reference architecture - Understand sizing and deployment options |
By Jason
