Data Science and Machine Learning Toolkit

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Save time, empower your teams and effectively upgrade your processes with access to this practical Data Science and Machine Learning Toolkit and guide. Address common challenges with best-practice templates, step-by-step work plans and maturity diagnostics for any Data Science and 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 Data Science and Machine Learning specific requirements:


STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Data Science and 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 998 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data Science and Machine Learning improvements can be made.

Examples; 10 of the 998 standard requirements:

  1. Who knew that it takes a lot of high quality data to properly train an artificial intelligence and that better data means better data science and more opportunities to monetize the data?

  2. When selecting a new cybersecurity related tool, how important is it that the manufacturer advertises its use of AI or machine learning applications to deliver its service?

  3. Should you invest in rapidly building up capabilities to execute complex machine learning models and provide real time decisions and optimized account level pricing?

  4. How do from in which is expected survival time it is that project, machine learning algorithms will contain generic inductive biases for your own or theme will work?

  5. Do you have one information system that can supply unified data from all sources for advanced analytics, machine learning, and artificial intelligence initiatives?

  6. Can machine learning techniques identify categories of sites in overhead imagery, based on the input of known dimensions and/or shape of an object or facility?

  7. When you have your organization problem which indicates that machine learning could be used, what is the first step for your investigation of the potential?

  8. How does your organization remain the decision maker on data usage in public–private partnerships or in data driven projects that impact the common good?

  9. Do you customize the machine learning model for your specific business needs without sacrificing growth or negatively impacting the customer experience?

  10. Do you comment on simulation process and data management, simulation driven data science applications as key enablers for democratization of simulation?


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 Data Science and Machine Learning book in PDF containing 998 requirements, which criteria correspond to the criteria in...

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

  • 62 step-by-step Data Science and Machine Learning Project Management Form Templates covering over 1500 Data Science and Machine Learning project requirements and success criteria:

Examples; 10 of the check box criteria:

  1. Human Resource Management Plan: Are Data Science and Machine Learning project team members involved in detailed estimating and scheduling?

  2. Contractor Status Report: What was the budget or estimated cost for your organizations services?

  3. Procurement Audit: Is the purchasing department facility laid out to facilitate interviews with salespersons?

  4. Project Performance Report: To what degree can the team measure progress against specific goals?

  5. Quality Management Plan: How does your organization maintain a safe and healthy work environment?

  6. Stakeholder Management Plan: Are updated Data Science and Machine Learning project time & resource estimates reasonable based on the current Data Science and Machine Learning project stage?

  7. Project Scope Statement: If the scope changes, what will the impact be to your Data Science and Machine Learning project in terms of duration, cost, quality, or any other important areas of the Data Science and Machine Learning project?

  8. Change Request: Can you answer what happened, who did it, when did it happen, and what else will be affected?

  9. Stakeholder Management Plan: Can you perform this task or activity in a more effective manner?

  10. Risk Audit: Do you ensure the recommended rules of play and protocols are followed for your activity?

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

1.0 Initiating Process Group:

  • 1.1 Data Science and Machine Learning project Charter
  • 1.2 Stakeholder Register
  • 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:

  • 2.1 Data Science and 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 Data Science and 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 Data Science and 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 Data Science and 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 Data Science and 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 Data Science and Machine Learning project with this in-depth Data Science and Machine Learning Toolkit.

In using the Toolkit you will be better able to:

  • Diagnose Data Science and 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 Data Science and 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 Data Science and Machine Learning investments work better.

This Data Science and 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.