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Guarantee your C1000-136 exam success with examkiller's study guide. The C1000-136 practice test questions are developed by experiences IBM Certification Professionals who working in todays prospering companies and IBM exam data center.

Exam Number: C1000-136

Exam Title: IBM Cloud Pak for Data v4.x Solution Architecture

Format: Single and Multiple Choice

Duration: 90 Minutes

Number of Questions: 63

Number of questions to pass: 42

Passing Score: 67%

Origin Provider: ExamKiller

Total Questions: 63 QAs

Type: Real Exam Questions

Guarantee: 100% Pass Guarantee

Demo: Click Here for Check Demo

IBM C1000-136 Exam Objectives

• Section 1: Cloud Pak for Data Architecture 21%
  1. Understand the underlying infrastructure and installation
  2. Understand sizing and deployment options
  3. Understand Cloud Pak for Data reference architecture
  4. Understand Cloud Pak for Data reliability options
  5. Secure the solution and client data
• Section 2: Build Data Science algorithms 14%
  1. Describe the differences between traditional programming and machine learning as well as no code, low code and visual programming
  2. Understand the process and available tools in Cloud Pak for data to build, deploy and monitor ML/AI algorithms
  3. Identify and explain how to collect, explore, and prepare data for ML/AI algorithms in Cloud Pak for Data
  4. Identify and explain how to build and deploy ML/AI algorithms in Cloud Pak for data
  5. Map business opportunities into a Data Science use case
• Section 3: Machine Learning Operations 16%
  1. Describe the key considerations when selecting a platform for model deployment
  2. Explain the workflow of deploying and monitoring models
  3. Monitor deployed models inside Cloud Pak for Data
  4. Monitor machine learning models running on an external platform
  5. Manage risk and regulatory compliance using Open Pages
• Section 4: Analytics 17%
  1. Explain the difference between Descriptive, Prescriptive, Predictive, Diagnostic, and Cognitive Analytics
  2. Describe the capabilities of AI for financial operations in Cloud Pak for Data
  3. Describe the capabilities of business intelligence in Cloud Pak for Data
  4. Map business opportunities into an Analytics use case
• Section 5: Data Governance 22%
  1. Describe the capabilities of a data fabric topology
  2. Define the Governance structure
  3. Use smart ingestion for auto cataloging
  4. Understand how workflow is used in Cloud Pak for Data
  5. Explain the use of Guardium in auditing and monitoring data
  6. Leverage the platform to understand data flow and usage
  7. Explain the concepts of Knowledge Accelerators
  8. Map business opportunities into a data governance use case
• Section 6: Integration, Implementation, Deployment, and Scaling 10%
  1. Develop an appropriate process to take a Data and AI solution from inception to production
  2. Develop a strategy to monitor the Data and AI platform
  3. Accelerate the solution using Industry Accelerators and External Data sets
  4. Integrating Business Applications using Cloud Pak for Data

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