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How Google Does Machine Learning

How Google Does Machine Learning


What is machine learning, and what kinds of problems can it solve? Google thinks about machine learning slightly differently – of being about logic, rather than just data. We talk about why such a framing is useful when thinking about building a pipeline of machine learning models. Then, we discuss the five phases of converting a candidate use case to be driven by machine learning, and consider why it is important the phases not be skipped. We end with a recognition of the biases that machine learning can amplify and how to recognize those biases.

What you will learn:

  • Frame a business use case as a machine learning problem.
  • Gain a broad perspective of machine learning and where it can be used.
  • Convert a candidate use case to be driven by machine learning.
  • Recognize biases that machine learning can amplify.
  • Leverage Google Cloud Platform tools and environment to do machine learning.

Who this course is for?

  • Aspiring machine learning data scientists and engineers
  • Machine learning scientists, data scientists, and data analysts
  • Data engineers



  • Some familiarity with basic machine learning concepts
  • Basic proficiency with a scripting language: Python preferred


Course Outline

  • Module 1: Introduction to Course
    • Summarize course scope
    • Get started with Google Cloud and Qwiklabs
  • Module 2: What it means to be AI first
    • Identify and solve ML problems such as intelligent search and natural speech processing to infuse applications with ML, build a data strategy, and use ML creatively.
    • Use ML creatively, to delight your users.
  • Module 3: How Google does ML
    • Acquire the organizational know-how to implement machine learning.
    • Leverage Google’s experience to avoid common pitfalls.
  • Module 4: Inclusive ML
    • Discover where bias in machine learning models originates.
    • Diagnose ML models with biases
  • Module 5: Python Notebooks in the Cloud
    • Run Cloud AI Platform (CAIP) Notebooks
    • Understand the development process using CAIP
    • Describe computation and storage
  • Module 6: Course Summary
    • Summarize Course

Jadwal Training

Tanggal Pukul Biaya (per pax; belum termasuk VAT 10%) Trainer Venue Daftar
TBA TBA Rp 14 juta Satria Yuda Utama Online TBA
TBA TBA Rp 14 juta Satria Yuda Utama Online TBA
TBA TBA Rp 14 juta Satria Yuda Utama Online TBA
TBA TBA Rp 14 juta Satria Yuda Utama Online TBA
TBA TBA Rp 14 juta Satria Yuda Utama Online TBA

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