CPMAI Methodology Phase III: Data Preparation

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In this course we’ll walk you through Phase III of the CPMAI Methodology. In this phase, we’ll help you with data preparation including reviewing feature enhancement and pruning, rationale for dataset inclusion / exclusion, data cleansing report, and other associated data preparation steps needed. You’ll gain an understanding of AI project management including product development & prototyping and learn best practice for implementing AI on a large scale as well as AI’s impact on strategy. This intermediate level course is geared towards executives or managers running AI projects and looking for best practices and methodologies.

What Will I Learn?

  • Data engineering and preparation
  • Data Preparation: Questions to Answer
  • Data Engineering Tasks
  • AI-Specific Needs of Data Preparation
  • Dataset Preparation & Pre-Processing
  • Cleaning & Enhancing Data
  • Data Selection / Sampling
  • Labeling Data

Who is this Training For?

  • Data engineering and preparation
  • Data Preparation: Questions to Answer
  • Data Engineering Tasks
  • AI-Specific Needs of Data Preparation
  • Dataset Preparation & Pre-Processing
  • Cleaning & Enhancing Data
  • Data Selection / Sampling
  • Labeling Data

Supported Learning Paths

  • Cognilytica: CPMAI Certification
  • DoD JAIC: Drive AI, Create AI
  • Edison DSF: Data Science Managers (DSP01 -DSP03)

Learning Levels

  • DoD JAIC AI: Intermediate (Applied) Level
  • Edison DSF: Level 3-4
  • Category: Implementing AI