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Advanced Data Science Governance for Big Data, Machine Learning & AI

Exam Details

  • Exam Code: DG90.01
  • Those who achieve this certification receive an official Digital Certificate of Excellence, as well as a Digital Certification Badge from Acclaim/Credly, with an account that supports the online verification of certification status.

Price

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This course is the second of three courses you must take to pursue the Data Science Governance Specialist certification.In this course, over 80 additional data science governance precepts and processes are described in relation to analytics platform governance and machine learning and AI pipeline governance stages.

Key Outcomes:
After this course you will know:

  • Ingress (including Source Data Access Constraints Assessment, Downstream Data Usage Analysis, etc.)
  • Data Lake (including Data Compression Template, Data Storage Lifecycle Definition, etc.)
  • Processing (including Processing Engine Standardization, Cluster Scaling Automation, etc.)
  • Data Warehouse (including On-demand Subject Access Request Compliance, SQL-based ML Model Version Control)
  • Problem Definition (including Adoption Risk Assessment, Project Budget Allocation)
  • Data Identification (including Organizational Data Regulations Adherence, Data Sensitivity Analysis, etc.)
  • etc

Objectives

  • Problem Definition (including Adoption Risk Assessment, Project Budget Allocation)
  • Data Identification (including Organizational Data Regulations Adherence, Data Sensitivity Analysis, etc.)
  • Data Extraction (including Data Extraction Policy, Automated Data Access, etc.)
  • Exploratory Data Analysis (EDA) (including Data Discrepancy Notification, Summary Statistics Registration, etc.)
  • Data Validation (including Statistical Fingerprint Drift Threshold, Data Validation Logic Automation, etc.)
  • Data Preparation (including Feature Engineering Guidelines, Data Preparation Logic Unit Test Automation, etc.)
  • Model Training (including Algorithm Selection Criteria, Training Metrics Registration, etc.)
  • Model Testing (including Model Passing Threshold, Model Testing Automation, etc.)
  • Model Deployment (including Model Version Switching Rules, Model Execution Dependencies Assessment, etc.)
  • Model Monitoring (including Model Performance Degradation Notification, Model Performance Review, etc.)
  • Model Retraining (Model Retraining Triggers and Model Retraining Metadata Registration)

Contact

  • Nurman (+62 857-2375-3840)
  • Irna (+62 822-1664-7749)
  • Puji (+62 813-2424-2115)
  • Shafa (+62 813-9049-0664)