Google Cloud for Machine Learning 2020 Master 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