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How to Deliver PSO Cloud Plan

Want to understand how to guide your customer through the technical and architectural design work of planning their move to the cloud? Then this course is for you.
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3 day course
Virtual, Private
Virtual Classroom
A convenient and interactive learning experience, that enables you to attend on of our courses from the comfort of your own home or anywhere you can log on. We offer Virtual Classroom on selected live classroom courses where this will appear as an option under the location drop down if available. These can also be booked as Private Virtual Classrooms for exclusive business sessions.
Private
A private training session for your team. Groups can be of any size, at a location of your choice including our training centres.
Supporting material

Learn how to deliver the Cloud Plan service offering to your customers, helping them map out an optimal and effective transition plan.

As a trusted Google Cloud partner, Jellyfish has been selected by Google to facilitate the delivery of this three-day instructor led course.

This Cloud Plan course helps customers build a strategic plan for their move to the cloud, looking at all the considerations for creating a solid foundation for their solution.

Our practitioner will facilitate technical kickoff workshops to discuss cloud infrastructure and data concepts, and give guidance on technical and architectural design. Together with the customer they assess viable use cases, document requirements and create a plan and timeline for executing the actual build.

At the end of the Cloud Plan, the customer will have a technical design document and a project plan to execute the solution on GCP.

This course is offered as a private training session and will run over three consecutive days. It can be delivered at our own training facilities in San Francisco or Baltimore, any location of your choice or via Virtual Classroom.

Course overview
Who should attend:
This course is aimed at Google Cloud Partners in the following relevant job roles: Cloud Consultants, Technical Project Leads, Cloud Architects, Cloud Engineers, Customer Success Managers and Technical Account Managers.
Walk away with the ability to:
  • Make use of the PSO Methodology for your customers cloud journey
  • Explain the value of the Cloud Plan service offering
  • Develop the skills necessary to deliver a Cloud Plan kickoff sessions
  • Recognise the best practices and watchpoints for different practice areas
  • Identify the key deliverables and logistical elements of delivering Cloud Plan
  • Locate and use the resources available to you when delivering Cloud Plan
Prerequisites:
Before attending this course you will need to have cloud consulting experience and be a Google Certified Professional, either certified in Cloud Architect or Data Engineer. You will need to have access to Cloud Connect - Partners and should have complete the Introduction to PSO Methodology online training.
It’s recommended you complete the Architecting with Google Cloud Platform: Design and Process course prior to taking this course.
Course agenda
Module 1: PSO Methodology Review
  • Why Cloud Discover: ML?
  • When to do Cloud Discover: ML?
  • Who are the key participants?
  • What is the scope of the service offering?
Module 2: Machine Learning overview
  • Machine learning lifecycle
  • Principles of Innovation at Google
  • What is machine learning?
  • The importance of data
Module 3: Cloud Discover Ideation Exercise
  • Business problem and use case identification
  • Positioning business challenges based on feasibility
  • Brainstorming ML use cases
  • Categorizing the ML use cases
  • Assessing business value of implementation
Module 4: Data Exploration
  • Data understanding and transformation
  • Identifying data sources
  • Data SME interviews
  • Data qualification
Module 5: Analysis and Recommendations
  • Overview of summary report
  • Qualification and analysis of top use cases
  • Create recommendations and comparison chart for summary report
Module 6: Next Steps and Wrap-up
  • Overview of Cloud Deploy: Machine Learning for Minimum Viable Model (MVM)
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