Google Cloud
Machine Learning on Google Cloud Specialization
Google Cloud

Machine Learning on Google Cloud Specialization

Learn machine learning with Google Cloud. Real-world experimentation with end-to-end ML

Included with Coursera Plus

Get in-depth knowledge of a subject

(8,582 reviews)

Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject

(8,582 reviews)

Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers

What you'll learn

  • Use Vertex AI AutoML and BigQuery ML to build, train, and deploy ML models

  • Implement machine learning models using Keras and TensorFlow 2.x

  • Implement machine learning in the enterprise best practices

  • Describe how to perform exploratory data analysis and improve data quality

Overview

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
20 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Google Cloud

Specialization - 4 course series

What you'll learn

  • Recognize the data-to-AI technologies and tools offered by Google Cloud.

  • Use generative AI capabilities in applications.

  • Choose between different options to develop an AI project on Google Cloud.

  • Build ML models end-to-end by using Vertex AI.

Skills you'll gain

Google Cloud Platform, Generative AI, Machine Learning, Prompt Engineering, MLOps (Machine Learning Operations), Natural Language Processing, Artificial Intelligence, Cloud Infrastructure, and Cloud Platforms

What you'll learn

  • Design and build a TensorFlow input data pipeline.

  • Use the tf.data library to manipulate data in large datasets.

  • Use the Keras Sequential and Functional APIs for simple and advanced model creation.

  • Train, deploy, and productionalize ML models at scale with Vertex AI.

Skills you'll gain

Keras (Neural Network Library), Google Cloud Platform, Tensorflow, Artificial Neural Networks, Deep Learning, Data Pipelines, Data Cleansing, Machine Learning, Application Programming Interface (API), Python Programming, Data Transformation, MLOps (Machine Learning Operations), and Cloud Computing

What you'll learn

  • Describe Vertex AI Feature Store and compare the key required aspects of a good feature.

  • Perform feature engineering using BigQuery ML, Keras, and TensorFlow.

  • Discuss how to preprocess and explore features with Dataflow and Dataprep.

  • Use tf.Transform.

Skills you'll gain

Feature Engineering, Data Transformation, Keras (Neural Network Library), Data Pipelines, Tensorflow, MLOps (Machine Learning Operations), Machine Learning, Data Processing, Real Time Data, Data Modeling, and Data Storage

What you'll learn

  • Describe data management, governance, and preprocessing options

  • Identify when to use Vertex AutoML, BigQuery ML, and custom training

  • Implement Vertex Vizier Hyperparameter Tuning

  • Explain how to create batch and online predictions, setup model monitoring, and create pipelines using Vertex AI

Skills you'll gain

Google Cloud Platform, Data Pipelines, Data Management, Workflow Management, MLOps (Machine Learning Operations), Tensorflow, Applied Machine Learning, Data Transformation, Machine Learning, Continuous Monitoring, Data Governance, and Cloud Computing

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Google Cloud Training
Google Cloud
1,992 Courses3,634,952 learners

Offered by

Google Cloud

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