Google Cloud for Machine Learning 2020 Master Course_1

Google Cloud for Machine Learning 2020 Master Course, available at $59.99, has an average rating of 4.5, with 74 lectures, based on 34 reviews, and has 292 subscribers.

You will learn about Learn the Essentials of Google Cloud Set up web apps using App Engine Create Virtual Machines on Google Cloud Deploy scalable applications on Google Cloud Create Cloud Functions using Python and Javascript Create event driven cloud functions Create a custom Compute Engine cluster Work with Firebase Database Understand the difference between SQL vs NoSQL architecture Create a fully managed Database offering Create Cloud BigQuery tables for storing Big Data Understand the SQL database query structure Understand the fundamentals of Git and GitHub Introduction to Machine Learning Introduction to Neural Networks Build and Deploy Machine Learning models on Google Cloud This course is ideal for individuals who are Anyone interested in cloud computing or Anyone interested in upgrading their Google Cloud skills It is particularly useful for Anyone interested in cloud computing or Anyone interested in upgrading their Google Cloud skills.

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Summary

Title: Google Cloud for Machine Learning 2020 Master Course

Price: $59.99

Average Rating: 4.5

Number of Lectures: 74

Number of Published Lectures: 74

Number of Curriculum Items: 74

Number of Published Curriculum Objects: 74

Original Price: $189.99

Quality Status: approved

Status: Live

What You Will Learn

Learn the Essentials of Google Cloud

Set up web apps using App Engine

Create Virtual Machines on Google Cloud

Deploy scalable applications on Google Cloud

Create Cloud Functions using Python and Javascript

Create event driven cloud functions

Create a custom Compute Engine cluster

Work with Firebase Database

Understand the difference between SQL vs NoSQL architecture

Create a fully managed Database offering

Create Cloud BigQuery tables for storing Big Data

Understand the SQL database query structure

Understand the fundamentals of Git and GitHub

Introduction to Machine Learning

Introduction to Neural Networks

Build and Deploy Machine Learning models on Google Cloud

Who Should Attend

Anyone interested in cloud computing

Anyone interested in upgrading their Google Cloud skills

Target Audiences

Anyone interested in cloud computing

Anyone interested in upgrading their Google Cloud skills

Cloud Computing is one of the highest paying and most demanding job category in technology. Most businesses in recent years have started using cloud services like database, networking, servers, analytics,and intelligence for their business needs. Using cloud services not only helps with smart usage of infrastructure but also minimizes operational costs.

Google Cloud is quickly gaining market adoption due to some of its offerings in the Data Analytics and Serverless domain. Looking at the future, Google Cloud would be an excellent choice.

This course aims at covering a lot of the most used Google cloud products.

1. App Engine:App Engine is one of Google Cloud’s serverless platforms. App Engine enables you to create infinitely scalable applications and deployments. In this section, you will be able to, Create an app engine project on Google Cloud. Host a static website on App Engine. Create an API using App Engine.

2. Cloud Functions: Cloud Functions is Google Cloud’s biggest offering in the abstracted serverless environment. Cloud functions make the deployment of simple and repeated tasks easier. In this section, you will be able to create a cloud function using Python and Javascript. You will also be able to use cloud functions as a middleware for App Engine and perform event driven tasks.

3. Cloud Compute Engine: Cloud compute engine is Google Cloud’s offering for the Virtual Machine space. You can create a Virtual machine with complete custom hardware and software. In this section, we will be creating a Virtual Machine on Google Cloud and create a CPU intensive program to benchmark the Virtual Machine.

4. Cloud Firestore: Cloud Firestore is a fully managed NoSQL database platform offered by Google Cloud and Firebase. We will be performing CRUD operations with Firebase and use it with App Engine.

5. Cloud BigQuery: Cloud BigQuery is Google Cloud’s offering for big data related workloads. In this section, we will be creating a custom dataset using Python, we will host this dataset on Cloud BigQuery and then perform SQL queries on the database

Overall, this course aims at providing a holistic understanding of the software development cycle on Google Cloud. Most of the essential steps from writing code to staging deployments using Git and GitHub are covered in this course.

Course Curriculum

Chapter 1: Getting started with Google Cloud

Lecture 1: Introduction

Lecture 2: What is a Cloud in 30 seconds

Lecture 3: Why Cloud Computing

Lecture 4: Virtualisation in a Cloud environment

Lecture 5: Introduction to git and github

Lecture 6: The environment

Lecture 7: Create an account of Google Cloud

Lecture 8: Creating a new Google Cloud Project

Lecture 9: Initialising App Engine on Google Cloud

Lecture 10: Git workflow

Lecture 11: Push code to GitHub

Lecture 12: Gcloud App Deploy

Lecture 13: Host a Website on Google Cloud

Chapter 2: Creating an API with App Engine

Lecture 1: Section deliverables

Lecture 2: What is a Network Protocol

Lecture 3: What is HTTP protocol ?

Lecture 4: Note on Python

Lecture 5: Hello World in Python on Google cloud

Lecture 6: Programming Language framework introduction

Lecture 7: Creating an API on Google Cloud

Lecture 8: Add parameters to URL

Lecture 9: Arrays in API

Lecture 10: API strings handler Python

Lecture 11: Section Recap

Chapter 3: Getting started with Compute Engine

Lecture 1: Section deliverables

Lecture 2: Local vs Remote compute platforms

Lecture 3: Compute Engine Problem statement

Lecture 4: Shell access to Compute Engine VM instance

Lecture 5: Resource Quantisation

Chapter 4: Getting started with Cloud Functions using Python

Lecture 1: Function Abstraction

Lecture 2: Cloud Function for Hello World

Lecture 3: Email Checker Function

Lecture 4: Section Recap

Chapter 5: Email Checker Project

Lecture 1: Section deliverables

Lecture 2: Introduction to CORS

Lecture 3: HTML boilerplate

Lecture 4: HTML page

Lecture 5: Note on JavaScript Basics

Lecture 6: JavaScript Basics

Lecture 7: Problem with CORS

Lecture 8: Adding CORS to cloud functions

Lecture 9: Deploying Cloud functions

Lecture 10: Completing the Project

Chapter 6: Getting started with Firebase

Lecture 1: Section deliverables

Lecture 2: Why use a Database

Lecture 3: Create a Database using Firestore

Lecture 4: Creating a service account key

Lecture 5: Initialising Firebase admin

Lecture 6: Read operation on Firestore using Python

Lecture 7: Update operation on Firestore using Python

Lecture 8: Create operation on Firestore using Python

Lecture 9: Delete operation on Firestore using Python

Chapter 7: Getting started with Cloud BigQuery

Lecture 1: Section Introduction

Lecture 2: Acquiring Data

Lecture 3: Generating CSV dataset using Python

Lecture 4: Simple SQL queries

Lecture 5: Compound SQL queries

Lecture 6: Exploring Public Datasets

Lecture 7: Python with BigQuery

Lecture 8: Section Recap

Chapter 8: Introduction to Machine Learning

Lecture 1: Section Introduction

Lecture 2: What are Neurons

Lecture 3: What are Weights

Lecture 4: What are Biases

Lecture 5: Activation Functions

Lecture 6: Application Specific Hardware (ASIC)

Chapter 9: Building a Machine Learning model on Google Cloud

Lecture 1: Section Introduction

Lecture 2: Machine Learning and the MNIST dataset

Lecture 3: Machine Learning workflow

Lecture 4: Creating a Compute Instance

Lecture 5: Implementing the Model

Lecture 6: Running the Project

Lecture 7: Course Conclusion

Lecture 8: BONUS Audio Lecture: Machine Learning by looking at nature

Instructors

Vinay Phadnis
CTO, Machine Learning & Quantum Consultant

Rating Distribution

1 stars: 1 votes

2 stars: 1 votes

3 stars: 5 votes

4 stars: 13 votes

5 stars: 14 votes

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