Completion Certificate for Machine Learning on Google Cloud

Completed by Hetav Kirit Pandya

July 1, 2020

Approximately 2 months at 10 hours a week to complete

Hetav Kirit Pandya's account is verified. Coursera certifies their successful completion of Google Cloud Machine Learning on Google Cloud Specialization.

Course Certificates Completed

How Google does Machine Learning

Machine Learning in the Enterprise

Launching into Machine Learning

Feature Engineering

Build, Train and Deploy ML Models with Keras on Google Cloud

Machine Learning on Google Cloud

Google Cloud

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95K Students Enrolled

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What you will 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

Skills you will gain

Tensorflow
Machine Learning
Feature Engineering
Cloud Computing
Vertex AI

View certificate for Hetav Kirit Pandya, Machine Learning on Google Cloud, offered through Coursera. In this five-course specialization, participants learn to build, train, and deploy Vertex AI AutoML and BigQuery ML models; create Vertex AI custom training jobs and deploy using Docker containers; use Feature Store; perform feature engineering; and choose data preprocessing options. They also learn to use Vertex Vizier hyperparameter tuning to add the right mix of parameters that yields accurate, generalized models and the theory to solve specific types of ML problems. They learn to write distributed ML models that scale in TensorFlow; and leverage best practices to implement machine learning on Google Cloud. They experimented with end-to-end ML — building an ML-focused strategy, then model training, optimization, and productionalization with hands-on labs using Google Cloud Platform.