Learn and demonstrate your ability to design, build, and implement machine-learning models through Google Cloud Professional Machine Learning Engineer Certification Course by Linkedin.

About Linkedin Learning

Learn business, creative, and technology skills to achieve your personal and professional goals through various professional skills-building courses offered by Linkedin.

Course Description

Earning the Google Professional Machine Learning Engineer certification demonstrates your ability to design, build, and productionize machine learning models to solve business challenges using Google Cloud technologies, and knowledge of proven ML models and techniques.

  • In the certification prep series, instructor Noah Gift covers core concepts relating to automating and orchestrating ML pipelines.
  • Noah explains how to design and implement training pipelines, including how to engineer prompts for Google BigQuery with ChatGPT4.
  • Then, learn about implementing serving pipelines, as Noah explains some of the characteristics of GPU-enabled Docker containers, gives a Rust PyTorch microservice walkthrough, and demos a Rust pre-trained PyTorch microservice.

Course Completion Highlights

  • Showcase on your LinkedIn profile under the “Licenses and Certificates” section
  • Download or print it out as PDF to share with others
  • Share an image online to demonstrate your skill

Course Content

  1. Designing and Implementing Training Pipelines
    • Prompt engineering for Google BigQuery with ChatGPT4
    • Getting started with Vertex AI
    • Understanding TPUs
    • TPUs as technology transition
    • Demo: TPU PyTorch MNIST
  2. Implementing Serving Pipelines
    • TensorFlow serving with GPU-enabled Docker
    • Rust PyTorch microservice walkthrough
    • Demo: Rust pre-trained PyTorch microservice

How to Apply?

Interested learners can join the course through this link.

Check other Machine Learning Courses on Linkedin

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Microsoft Azure Machine Learning Fundamentals

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Azure Machine Learning Development: Part 1

Mistakes to Avoid in Machine Learning

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