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Group: IBM Data and AI - Data and AI
Certification status: Live
PartnerWorld code: C0004601
Replaces PW code: C0004600
Being Replaced By: N/A
Required exam: IBM Cloud Pak for Data v4.x Solution Architecture
Exam status: Live
Certification Overview
An IBM Certified Solution Architect on Cloud Pak for Data V4.x is a person
who can design, plan and architect a Data and AI solution in a hybrid cloud
environment. This architect can lead and guide the implementation and
operationalization of a solution that may include Data Governance (Data Ops),
Analytics, and Data Science/Machine Learning/AI (ML Ops). They can do this with
limited assistance from support, documentation, and/or relevant subject matter
experts.
Requirements
Exam C1000-136: IBM Cloud Pak for Data v4.x Solution Architecture
Exam Objectives
During exam development, the Subject Matter Experts (SMEs) define all of the
tasks, knowledge and experience that an individual would need in order to
successfully fulfill their role with the product or solution. These are
represented by the objectives below and the questions on the exam are based upon
these objective.
Number of questions: 63
Number of questions to pass: 42
Time allowed: 90 minutes
Status: Live
Section 1: Cloud Pak for Data Architecture
Understand the underlying infrastructure and installation
Understand sizing and deployment options
Understand Cloud Pak for Data reference architecture
Understand Cloud Pak for Data reliability options
Secure the solution and client data
Section 2: Build Data Science algorithms
Describe the differences between traditional programming and machine learning as
well as no code, low code and visual programming
Understand the process and available tools in Cloud Pak for data to build,
deploy and monitor ML/AI algorithms
Identify and explain how to collect, explore, and prepare data for ML/AI
algorithms in Cloud Pak for Data
Identify and explain how to build and deploy ML/AI algorithms in Cloud Pak for
data
Map business opportunities into a Data Science use case
Section 3: Machine Learning Operations
Describe the key considerations when selecting a platform for model
deployment
Explain the workflow of deploying and monitoring models
Monitor deployed models inside Cloud Pak for Data
Monitor machine learning models running on an external platform
Manage risk and regulatory compliance using Open Pages
Section 4: Analytics
Explain the difference between Descriptive, Prescriptive, Predictive,
Diagnostic, and Cognitive Analytics
Describe the capabilities of AI for financial operations in Cloud Pak for Data
Describe the capabilities of business intelligence in Cloud Pak for Data
Map business opportunities into an Analytics use case
Section 5: Data Governance
Describe the capabilities of a data fabric topology
Define the Governance structure
Use smart ingestion for auto cataloging
Understand how workflow is used in Cloud Pak for Data
Explain the use of Guardium in auditing and monitoring data
Leverage the platform to understand data flow and usage
Explain the concepts of Knowledge Accelerators
Map business opportunities into a data governance use case
Section 6: Integration, Implementation, Deployment, and Scaling
Develop an appropriate process to take a Data and AI solution from inception to
production
Develop a strategy to monitor the Data and AI platform
Accelerate the solution using Industry Accelerators and External Data sets
Integrating Business Applications using Cloud Pak for Data
Exam Resources
All IBM certification tests presume a certain amount of "on-the-job" experience
which is not present in any classroom or Web presentation. The recommended
courses and links will help you gain the skill and product knowledge represented
in the test objectives. They do not teach the answers to the test questions and
are not intended to do so. This information may not cover all subject areas in
the certification test or may contain more recent information than is present in
the certification test. Taking these or any classes will not guarantee that you
will achieve certification.
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