Data Science


Tensorflow on Google's Cloud Platform for Data Engineers

The Fourth Course in a Series for Attaining the Google Certified Data Engineer

4.25 (44 reviews)

Tensorflow on Google's Cloud Platform for Data Engineers


1.5 hours


Aug 2017

Last Update
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What you will learn

You'll understand the basics of TensorFlow.

You'll be able to build TensorFlow models on Google's Cloud.

You'll be prepared for TensorFlow questions on the Google Certified Data Engineering Exam.

Upon completion you'll know how to build machine learning models inside Google's Cloud.


Welcome to Tensorflow on the Google Cloud Platform for Data Engineers This is the fourth course in a series of courses designed to help you attain the coveted Google Certified Data Engineer. 

Additionally, the series of courses is going to show you the role of the data engineer on the Google Cloud Platform

NOTE: This is not a course on how to develop machine learning models with TensorFlow. This is a very targeted course on TensorFlow for data engineers.  My goal is to give data engineers what they need to know for the exam and provide learners with the foundations of TensorFlow on Google's Cloud Platform. 

At this juncture the Google Certified Data Engineer is the only real world certification for data and machine learning engineers.

TensorFlow is an open source software library created by Goggle for doing graph-based computations quickly. It does this by utilizing the GPU(Graphics Processing Unit)  and also making it easy to distribute the work across multiple GPUs and computers.

Tensors, in general, are simply arrays of numbers, or functions, that transform according to certain rules under a change of conditions. Nodes in the graphs represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. 

In the course you'll discover how to apply TensorFlow to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessions and the computation graph.

You'll work with basic math operations and image transformations to see how common computations are performed.

You'll learn TensorFlow within the context of the Google Cloud Platform

                                                             *Five Reasons to take this Course.*

1) You Want to be a Data Engineer 

It's the number one job in the world. (not just within the computer space) The growth potential career wise is second to none. You want the freedom to move anywhere you'd like. You want to be compensated for your efforts. You want to be able to work remotely. The list of benefits goes on. 

2) The Google Certified Data Engineer 

Google is always ahead of the game. If you were to look back at a timeline of their accomplishments in the data space you might believe they have a crystal ball. They've been a decade ahead of everyone.  Now, they are the first and the only cloud vendor to have a data engineering certification. With their track record I'll go with Google. 

3) The Growth of Data is Insane 

Ninety percent of all the world's data has been created in the last two years. Business around the world generate approximately 450 billions transactions a day. The amount of data collected by all organizations is approximately 2.5 Exabytes a day. That number doubles every month. 

4) TensorFlow in Plain English

TensorFlow is a low level language.  The basic concept of a tenor is hard to grasp if you aren't familiar with neural networks. In the course we will break down TensorFlow in to bite sized pieces ensuring you learn the fundamentals first. After we've built a base understanding of tensors and how they flow we will move on to more complicated examples. 

5) You want to be ahead of the Curve 

The data engineer role is fairly new.  While your learning, building your skills and becoming certified you are also the first to be part of this burgeoning field.  You know that the first to be certified means the first to be hired and first to receive the top compensation package. 

Thank you for your interest in Tensorflow on the Google Cloud Platform for Data Engineers and we will see you in the course!!


Welcome to TensorFlow


Exam Update

Is this Course for You?

Instructor Course Q&A

What's an Array?

What is a Multi-Dimensional Array or Tensor?

How Tensors Flow

Real Numbers Flowing through our Graph

Hello World in TensorFlow

Course Downloads



Up and Running in Cloud Datalab

Creating Jupyter Notebooks on GCP

Reconnect to Datalab Virtual Machine

Download/Upload Notebooks to Datalab

Lab: Up and Running with Datalab



TensorFlow Basics

The TensorFlow Code Base

Forward Feeding Graphs

Handling Iteration in TensorFlow Graphs

2 Steps in Every TensorFlow Program

Modeling Larger Computational Graphs

Resizing After High Utilization Warning

Simple End to End Example

Tensor Dimensions


Session Parameters: Fetch and Feed_Dict

Node Life Cycle

Tensor Properties

Convert to Tensors

Enabling Logging with TensorFlow

Lab: Hello World in TensorFlow



TensorFlow Demos

Numpy Vs TensorFlow

Dataset Creation and Exploration

Data Wrangling

Linear Regression in TensorFlow

The Mandelbrot Set

Overfitting and How to Correct it

Using Cloud Machine Learning

Model Packaging

Creating a Server Input Function

Lab: Linear Regression in TensorFlow

Lab Review: Linear Regression


Section Quiz

Sample Exam Questions


John3 August 2019

Good course for learning what Tensorflow is and its concepts and general applications and concepts. I wish the course was a better introduction into practically learning to generate useful tensorflow.

Valentina20 October 2017

Excellent details and examples. The Tensorflow mappings showing how the tensors flow the data to the nodes for computation was very helpful.


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