Google
The Nuts and Bolts of Machine Learning
Google

The Nuts and Bolts of Machine Learning

This course is part of Google Advanced Data Analytics Professional Certificate

Taught in English

Some content may not be translated

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Course

Gain insight into a topic and learn the fundamentals

4.8

(317 reviews)

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98%

Advanced level
Designed for those already in the industry
36 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Identify characteristics of the different types of machine learning

  • Prepare data for machine learning models 

  • Build and evaluate supervised and unsupervised learning models using Python

  • Demonstrate proper model and metric selection for a machine learning algorithm

Details to know

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Assessments

22 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.8

(317 reviews)

|

98%

Advanced level
Designed for those already in the industry
36 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your Machine Learning expertise

This course is part of the Google Advanced Data Analytics Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate from Google
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There are 5 modules in this course

You’ll start by exploring the basic concepts of machine learning and the role of machine learning in data science. Then, you’ll review the four main types of machine learning: supervised, unsupervised, reinforcement, and deep learning.

What's included

16 videos7 readings7 quizzes2 plugins

You’ll learn how data professionals use a structured workflow for machine learning. You'll identify the main steps of the workflow and the importance of each step in the overall process. Then, you'll learn how to apply specific machine learning models to business problems.

What's included

12 videos6 readings3 quizzes6 ungraded labs

You’ll learn more about one of the major types of machine learning: unsupervised learning. You'll begin by exploring the difference between supervised and unsupervised techniques and the benefits and uses of each approach. Then, you’ll learn how to apply two unsupervised machine learning models: clustering and K-means.

What's included

7 videos4 readings3 quizzes4 ungraded labs

Next, you’ll focus on supervised learning. You’ll learn how to test and validate the performance of supervised machine learning models such as decision tree, random forest, and gradient boosting.

What's included

16 videos11 readings5 quizzes10 ungraded labs1 plugin

You’ll complete the final end-of-course project by applying different machine learning models to a workplace scenario dataset.

What's included

5 videos9 readings4 quizzes2 discussion prompts6 ungraded labs

Instructor

Instructor ratings
4.8 (79 ratings)
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Google
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4.8

317 reviews

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5

Reviewed on Jan 15, 2024

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5

Reviewed on Aug 21, 2023

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5

Reviewed on Jan 14, 2024

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