Managing Machine Learning Projects

This course is part of AI Product Management Specialization

Instructor: Jon Reifschneider

Skills you'll gain

  •   Technical Management
  •   MLOps (Machine Learning Operations)
  •   Software Versioning
  •   Data Science
  •   Artificial Intelligence and Machine Learning (AI/ML)
  •   Systems Architecture
  •   Data Cleansing
  •   Data Collection
  •   Data Quality
  •   Solution Design
  •   Machine Learning
  •   Software Development Life Cycle
  •   Applied Machine Learning
  •   Data Pipelines
  •   Data Processing
  •   Technology Solutions
  •   Data Management
  •   Feature Engineering
  • There are 5 modules in this course

    At the conclusion of this course, you should be able to: 1) Identify opportunities to apply ML to solve problems for users 2) Apply the data science process to organize ML projects 3) Evaluate the key technology decisions to make in ML system design 4) Lead ML projects from ideation through production using best practices

    Organizing ML Projects

    Data Considerations

    ML System Design & Technology Selection

    Model Lifecycle Management

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