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| Course Fee | 575 |
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575 (USD) |
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Koenig Learning Stack
Free Pre-requisite TrainingJoin a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.
Assessments (Qubits)Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.
Post Training ReportsReceive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.
Class RecordingsGet access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.
Free Lab ExtensionsExtend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.
Free Revision Classes Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
Asset Management Essentials in Jira Service Management - Live Team Training introduces your team to managing enterprise and IT assets within Jira, exploring CMDB capabilities, automation, and integration for improved asset management efficiency.
Introduction: The Asset Management Essentials in Jira Service Management Live Team Training course equips your team with the skills to manage Enterprise and IT assets effectively using Assets. The course covers UI navigation, object schemas creation, automation configuration, and data integration.
Learning Objectives and Outcomes:
