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The Art of Service Standard Requirements Self Assessments

Azure machine learning studio Toolkit: best-practice templates, step-by-step work plans and maturity diagnostics

$249.00

Azure machine learning studio Toolkit: best-practice templates, step-by-step work plans and maturity diagnostics

$249.00

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Product Description

Save time, empower your teams and effectively upgrade your processes with access to this practical Azure machine learning studio Toolkit and guide. Address common challenges with best-practice templates, step-by-step work plans and maturity diagnostics for any Azure machine learning studio related project.

Download the Toolkit and in Three Steps you will be guided from idea to implementation results.

The Toolkit contains the following practical and powerful enablers with new and updated Azure machine learning studio specific requirements:


STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Azure machine learning studio Self Assessment book in PDF containing 49 requirements to perform a quickscan, get an overview and share with stakeholders.

Organized in a data driven improvement cycle RDMAICS (Recognize, Define, Measure, Analyze, Improve, Control and Sustain), check the…

  • Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation

Then find your goals...


STEP 2: Set concrete goals, tasks, dates and numbers you can track

Featuring 839 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Azure machine learning studio improvements can be made.

Examples; 10 of the 839 standard requirements:

  1. Has/have the customer(s) been identified?

  2. Have you found any ground fruit or low-hanging fruit for immediate remedies to the gap in performance?

  3. What tools and technologies are needed for a custom Azure machine learning studio project?

  4. What stupid rule would we most like to kill?

  5. Does Azure machine learning studio appropriately measure and monitor risk?

  6. Are we Assessing Azure machine learning studio and Risk?

  7. Why are Azure machine learning studio skills important?

  8. How are you going to measure success?

  9. What are the rules and assumptions my industry operates under? What if the opposite were true?

  10. Who else should we help?


Complete the self assessment, on your own or with a team in a workshop setting. Use the workbook together with the self assessment requirements spreadsheet:

  • The workbook is the latest in-depth complete edition of the Azure machine learning studio book in PDF containing 839 requirements, which criteria correspond to the criteria in...

Your Azure machine learning studio self-assessment dashboard which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next:

  • The Self-Assessment Excel Dashboard; with the Azure machine learning studio Self-Assessment and Scorecard you will develop a clear picture of which Azure machine learning studio areas need attention, which requirements you should focus on and who will be responsible for them:

    • Shows your organization instant insight in areas for improvement: Auto generates reports, radar chart for maturity assessment, insights per process and participant and bespoke, ready to use, RACI Matrix
    • Gives you a professional Dashboard to guide and perform a thorough Azure machine learning studio Self-Assessment
    • Is secure: Ensures offline data protection of your Self-Assessment results
    • Dynamically prioritized projects-ready RACI Matrix shows your organization exactly what to do next:

 

STEP 3: Implement, Track, follow up and revise strategy

The outcomes of STEP 2, the self assessment, are the inputs for STEP 3; Start and manage Azure machine learning studio projects with the 62 implementation resources:

  • 62 step-by-step Azure machine learning studio Project Management Form Templates covering over 6000 Azure machine learning studio project requirements and success criteria:

Examples; 10 of the check box criteria:

  1. Responsibility Assignment Matrix: The staff characteristics Ð is the group or the person capable to work together as a team?

  2. Team Performance Assessment: How does Azure machine learning studio project termination impact Azure machine learning studio project team members?

  3. Planning Process Group: Is the identification of the problems, inequalities and gaps, with their respective causes, clear in the Azure machine learning studio project?

  4. Scope Management Plan: Does the title convey to the reader the essence of the Azure machine learning studio project?

  5. Change Management Plan: Does this change represent a completely new process for the organization, or a different application of an existing process?

  6. Planning Process Group: How are the principles of aid effectiveness (ownership, alignment, management for development results and mutual responsibility) being applied in the Azure machine learning studio project?

  7. Team Performance Assessment: To what degree do team members articulate the teams work approach?

  8. Procurement Audit: Is it tested periodically, whether the organizations way of handling tasks is competitive in relation to price and quality?

  9. Procurement Audit: Are known obligations, such as salaries and contracts, encumbered at the beginning of the year?

  10. Executing Process Group: Will a new application be developed using existing hardware, software, and networks?

 
Step-by-step and complete Azure machine learning studio Project Management Forms and Templates including check box criteria and templates.

1.0 Initiating Process Group:

  • 1.1 Azure machine learning studio project Charter
  • 1.2 Stakeholder Register
  • 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:

  • 2.1 Azure machine learning studio project Management Plan
  • 2.2 Scope Management Plan
  • 2.3 Requirements Management Plan
  • 2.4 Requirements Documentation
  • 2.5 Requirements Traceability Matrix
  • 2.6 Azure machine learning studio project Scope Statement
  • 2.7 Assumption and Constraint Log
  • 2.8 Work Breakdown Structure
  • 2.9 WBS Dictionary
  • 2.10 Schedule Management Plan
  • 2.11 Activity List
  • 2.12 Activity Attributes
  • 2.13 Milestone List
  • 2.14 Network Diagram
  • 2.15 Activity Resource Requirements
  • 2.16 Resource Breakdown Structure
  • 2.17 Activity Duration Estimates
  • 2.18 Duration Estimating Worksheet
  • 2.19 Azure machine learning studio project Schedule
  • 2.20 Cost Management Plan
  • 2.21 Activity Cost Estimates
  • 2.22 Cost Estimating Worksheet
  • 2.23 Cost Baseline
  • 2.24 Quality Management Plan
  • 2.25 Quality Metrics
  • 2.26 Process Improvement Plan
  • 2.27 Responsibility Assignment Matrix
  • 2.28 Roles and Responsibilities
  • 2.29 Human Resource Management Plan
  • 2.30 Communications Management Plan
  • 2.31 Risk Management Plan
  • 2.32 Risk Register
  • 2.33 Probability and Impact Assessment
  • 2.34 Probability and Impact Matrix
  • 2.35 Risk Data Sheet
  • 2.36 Procurement Management Plan
  • 2.37 Source Selection Criteria
  • 2.38 Stakeholder Management Plan
  • 2.39 Change Management Plan


3.0 Executing Process Group:

  • 3.1 Team Member Status Report
  • 3.2 Change Request
  • 3.3 Change Log
  • 3.4 Decision Log
  • 3.5 Quality Audit
  • 3.6 Team Directory
  • 3.7 Team Operating Agreement
  • 3.8 Team Performance Assessment
  • 3.9 Team Member Performance Assessment
  • 3.10 Issue Log


4.0 Monitoring and Controlling Process Group:

  • 4.1 Azure machine learning studio project Performance Report
  • 4.2 Variance Analysis
  • 4.3 Earned Value Status
  • 4.4 Risk Audit
  • 4.5 Contractor Status Report
  • 4.6 Formal Acceptance


5.0 Closing Process Group:

  • 5.1 Procurement Audit
  • 5.2 Contract Close-Out
  • 5.3 Azure machine learning studio project or Phase Close-Out
  • 5.4 Lessons Learned

 

Results

With this Three Step process you will have all the tools you need for any Azure machine learning studio project with this in-depth Azure machine learning studio Toolkit.

In using the Toolkit you will be better able to:

  • Diagnose Azure machine learning studio projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices
  • Implement evidence-based best practice strategies aligned with overall goals
  • Integrate recent advances in Azure machine learning studio and put process design strategies into practice according to best practice guidelines

Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role; In EVERY company, organization and department.

Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?'

This Toolkit empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Azure machine learning studio investments work better.

This Azure machine learning studio All-Inclusive Toolkit enables You to be that person.

 

Includes lifetime updates

Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

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