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The Art of Service Standard Requirements Self Assessments

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Amazon Machine Learning Toolkit: best-practice templates, step-by-step work plans and maturity diagnostics

$249.00

Amazon Machine Learning 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 Amazon Machine Learning Toolkit and guide. Address common challenges with best-practice templates, step-by-step work plans and maturity diagnostics for any Amazon Machine Learning 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 Amazon Machine Learning specific requirements:


STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Amazon Machine Learning 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 802 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Amazon Machine Learning improvements can be made.

Examples; 10 of the 802 standard requirements:

  1. How are you going to measure success?

  2. How does the Amazon Machine Learning manager ensure against scope creep?

  3. What are strategies for increasing support and reducing opposition?

  4. How do you identify and analyze stakeholders and their interests?

  5. What to do with the results or outcomes of measurements?

  6. Describe the design of the pilot and what tests were conducted, if any?

  7. Do you keep 50% of your time unscheduled?

  8. Have the types of risks that may impact Amazon Machine Learning been identified and analyzed?

  9. Does Amazon Machine Learning analysis isolate the fundamental causes of problems?

  10. How likely is the current Amazon Machine Learning plan to come in on schedule or on budget?


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 Amazon Machine Learning book in PDF containing 802 requirements, which criteria correspond to the criteria in...

Your Amazon Machine Learning 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 Amazon Machine Learning Self-Assessment and Scorecard you will develop a clear picture of which Amazon Machine Learning 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 Amazon Machine Learning 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 Amazon Machine Learning projects with the 62 implementation resources:

  • 62 step-by-step Amazon Machine Learning Project Management Form Templates covering over 6000 Amazon Machine Learning project requirements and success criteria:

Examples; 10 of the check box criteria:

  1. Risk Management Plan: What is the impact to the Amazon Machine Learning project if the item is not resolved in a timely fashion?

  2. Project Scope Statement: What should you drop in order to add something new?

  3. Variance Analysis: When, during the last four quarters, did a primary business event occur causing a fluctuation?

  4. Activity Duration Estimates: How difficult will it be to do specific activities on this Amazon Machine Learning project?

  5. Activity Duration Estimates: What are some of the ways to create and distribute Amazon Machine Learning project performance information?

  6. Quality Management Plan: Do trained quality assurance auditors conduct the audits as defined in the Quality Management Plan and scheduled by the Amazon Machine Learning project manager?

  7. Risk Audit: Is there (or should there be) some impact on the process of setting materiality when the auditor more effectively identifies higher risk areas of the financial statements?

  8. Change Request: Has a formal technical review been conducted to assess technical correctness?

  9. Assumption and Constraint Log: Model-building: What data-analytic strategies are useful when building proportional-hazards models?

  10. Requirements Management Plan: The WBS is developed as part of a Joint Planning session. But how do you know that youve done this right?

 
Step-by-step and complete Amazon Machine Learning Project Management Forms and Templates including check box criteria and templates.

1.0 Initiating Process Group:

  • 1.1 Amazon Machine Learning project Charter
  • 1.2 Stakeholder Register
  • 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:

  • 2.1 Amazon Machine Learning project Management Plan
  • 2.2 Scope Management Plan
  • 2.3 Requirements Management Plan
  • 2.4 Requirements Documentation
  • 2.5 Requirements Traceability Matrix
  • 2.6 Amazon Machine Learning 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 Amazon Machine Learning 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 Amazon Machine Learning 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 Amazon Machine Learning 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 Amazon Machine Learning project with this in-depth Amazon Machine Learning Toolkit.

In using the Toolkit you will be better able to:

  • Diagnose Amazon Machine Learning 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 Amazon Machine Learning 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 Amazon Machine Learning investments work better.

This Amazon Machine Learning 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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