Blockchain Bootcamp for Data Scientists

Cílová skupina

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This course is intended for technical leaders who make technical decisions about their data science architecture, analytical environments, and organizational insights delivery.

Struktura kurzu

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• How we got to now: the digital data transformation
  • The origin of data-driven approaches in government, academia and business
  • Progress in data factor markets
    • Data connectivity
    • Data storage
    • Data processing
  • Quantification of everything
    • IoT
    • Smart Cities
    • Wearables
  • A brave new world of perfect information
• Where data science is headed: the coming datapocalypse
  • The dependency of data science on the theory of variance
  • Why data centralization will kill traditional data science
  • Why most organizations are ill prepared for the coming wave of data
  • Why most organizations are totally unprepared for blockchain data
• Why blockchain is the solution for data science
  • Blockchain as a data engineering solution
    • Defined quantification
    • Data completeness
    • Data trustworthiness
  • Blockchain as a data analytics solution
    • Data access and preparation
    • Data scope and data totality improvements
    • New data science frameworks
• Examples of successful blockchain data science projects
  • Use cases by vertical
    • Finance
    • Ecommerce
    • Healthcare
    • Fintech & SaaS
  • Use cases by organizational type
    • SMBs
    • Enterprises
    • Government
    • NGOs
  • Use cases by organizational department
    • Business Intelligence
    • Marketing
    • Customer Experience Management
    • Procurement & Fulfillment

• How to get started with your first blockchain-based data science project
  • Offensive strategies for adopting blockchain into data science workflows
    • Data maturity stage audit
    • Prioritizing blockchain data science projects
    • Build or buy blockchain data science solutions
  • Defensive strategies for adopting blockchain into data science workflows
    • Competitive intelligence and secondary research
    • Macro metric correlations for blockchain data science models
    • Game theory and “best response” actions