End-to-End Machine Learning with TensorFlow on GCP

Course Modality

Instructor-led (classroom)

Course Level

Advanced

Course Time

13 hours

Course Language

English

Course Overview

In the first course of this specialization, we will recap what was covered in the Machine Learning with TensorFlow on Google Cloud Platform Specialization (https://www.coursera.org/specializations/machine-learning-tensorflow-gcp).

One of the best ways to review something is to work with the concepts and technologies that you have learned. So, this course is set up as a workshop and in this workshop, you will do End-to-End Machine Learning with TensorFlow on Google Cloud Platform

Prerequisites

  • Basic SQL, familiarity with Python and TensorFlow

Why The DataTech Labs ?

Self-Paced Online Video

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A 360-degree learning approach that you can adapt to your learning style

Engage and learn more with these live and highly-interactive classes alongside your peers

24/7 Teaching Assistance

24/7 Teaching Assistance Keep engaged with integrated teaching

Online Practice Labs

Projects provide you with sample work to show prospective employers.

Applied Projects

Real-world projects relevant to what you’re learning throughout the program

Learner Social Forums

A support team focused on helping you succeed alongside a peer community

Course Curriculum

Welcome to the Course

We’ll give you an overview of this course and reveal the upcoming Advanced Machine Learning with TensorFlow on GCP specialization.

Machine Learning (ML) on Google Cloud Platform (GCP)

This module reviews the steps of deploying machine learning in a production environment

Explore the Data

This module explores a large dataset using Datalab and BigQuery.

Create the dataset

This modules shows how to use Pandas in Datalab and sample a dataset for local development.

Build the Model

This module let’s you develop a machine learning model in Tensorflow.

Operationalize the model

This module explains how to preprocess data at scale for machine learning and lets you train a machine learning model at scale on Cloud AI Platform.

Summary

This module reviews what you’ve learned in this course.

Recommended Exams

Machine Learning Engineer

Professional Machine Learning EngineerBETA

A Professional Machine Learning Engineer designs, builds, and productionizes ML models to solve business challenges using Google Cloud technologies and knowledge of proven ML models and techniques. The ML Engineer is proficient in all aspects of model architecture, data pipeline interaction, and metrics interpretation and needs familiarity with application development, infrastructure management, data engineering, and security.

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