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Managing Machine Learning projects with Google Cloud (MMLPGC)

 

Course Overview

Business professionals in non-technical roles have a unique opportunity to lead and influence machine learning projects. In this course, you'll explore machine learning without the technical jargon. You'll learn how to translate business problems into custom machine learning use cases, assess each phase of the project, and translate the requirements to your technical team.

Who should attend

  • Enterprise, corporate, or SMB business professionals in non-technical roles. Roles include but are not limited to: business analysts, IT managers, project managers, and product managers.
  • For senior VPs and above, Data-Driven Transformation with Google Cloud (ILT) is more suitable.

Prerequisites

  • No prior technical knowledge is required.
  • Savvy about your own business and objectives.
  • Recommended: Business Transformation with Google Cloud (on-demand).

Course Objectives

  • Thoroughly understand how ML can be used to improve business processes and create new value.
  • Explore common machine learning use cases implemented by businesses.
  • Identify the requirements to carry out an ML project, from assessing feasibility, to data preparation, model training, evaluation, and deployment.
  • Define data characteristics and biases that affect the quality of ML models.
  • Recognize key considerations for managing ML projects, including data strategy, governance, and project teams.
  • Pitch a custom ML use case that can meaningfully impact your business.
Online Training

Duration 2 days

Price (excl. tax)
  • 1,300.— €
Digital courseware
Classroom Training

Duration 2 days

Price (excl. tax)
  • Germany: 1,300.— €
  • Switzerland: CHF 1,700.—
incl. catering Digital courseware
 

Schedule

Instructor-led Online Training:   Course conducted online in a virtual classroom.
English
Time zone: Central European Summer Time (CEST)   ±1 hour
Online Training Time zone: British Summer Time (BST)
Online Training Time zone: Greenwich Mean Time (GMT)
 
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