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37

Becoming a Cloud Expert: Microsoft Azure IaaS - Level 2

Monitor the Performance, Health, & Availability of Azure Services and Your Cloud Resources

By Idan Gabrieli | in Online Courses

Microsoft Azure is one of the leading cloud providers (together with Amazon AWS and Google Cloud) with a global cloud infrastructure for providing public cloud services around the world. If you are looking to become a cloud expert then this training program is designed to help you build the knowledge and experience about the subject of cloud computing while using the Azure cloud platform. In this course, you'll learn how to monitor and analyze the performance and health of Azure resources and applications as well as Azure platform and services.

  • Access 37 lectures & 3 hours of content 24/7
  • Understand the different types of telemetry data (metrics & logs) that can be collected
  • Build your own demo system in Azure (using Linux, Apache, MySqL, PHP)
  • Setup alert rules & action groups for creating an automation layer
  • Simulate traffic load on the demo system
  • Monitor the status of Azure platform & services
  • Analyze performance metrics in multiple layers
  • Manage the life cycle of Azure alerts

Instructor

Arduino Developers Academy (ADA) is an education program dedicated to Arduino developers and Internet of Things (IoT) makers who are keen on building cool electronics projects that combine low cost hardware components like sensors, LCDs, keyboards while using the Arduino development environment.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels

Requirements

  • Internet required

Course Outline

  • Getting Started
    • Welcome - 3:43
    • Course Objectives and Structure - 4:04
    • Why - 6:03
    • What - 5:13
    • How - 3:27
  • Telemetry Data Collection - Types and Sources
    • Section 2 - Overview - 1:15
    • Data Sources - Collection from Multiple Layers - 5:56
    • Metrics and Logs - 5:05
    • Data Type #1 - Azure Subscription-Level Activity Log - 4:24
    • Data Type #2 - Azure Resources Diagnostics Logs - 1:36
    • Data Type #3 - Azure Resources Metrics - 3:45
    • Data Type #4 - Guest OS Metrics and Logs - 2:02
    • Data Type #5 - Applications Metrics and Logs - 2:18
    • Test Your Knowledge - Telemetry Data
  • Preparing our Demo System "Playground"
    • Section 03 - Overview - 4:43
    • Step 1 – Back-End MySQL DB Server - 14:03
    • Step 2 - Front-End Apache Web Server - 11:15
    • Step 3 - Log Analytics Workspace - 2:51
    • Step 4 - Diagnostics Settings - 4:29
    • Step 5 - Azure Monitor for VMs - 2:59
    • Step 6 - Application Insights - 7:26
  • Effective Monitoring is all about Automation
    • Section 4 - Overview - 4:24
    • The Concept of Alerts and Actions - 4:57
    • How to Create an Alert Rule - 9:17
    • Configure Our Rules and Actions - 12:04
    • Simulating a Load on the Web Server - 4:48
    • Managing Alerts - 5:31
    • Test Your Knowledge - Automation
  • Monitoring the Azure Platform
    • Section 5 - Overview
    • Azure Global Status - 3:47
    • Personalized Service Health - 9:31
  • Monitoring our Azure Solution
    • Section 6 - Overview - 2:26
    • Review the Status, Health and Activity Logs - 3:18
    • Metrics Explorer - 5:12
    • Log Analytics - 15:13
    • Azure Monitor for VMs - 9:38
    • Azure Advisor - 1:51
    • Application Insights - 9:45
    • Test Your Knowledge - Monitoring our Azure Solution
  • Course Summary
    • A Quick Recap - 8:31

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5 hours
Lessons
43

Becoming a Cloud Expert: Microsoft Azure IaaS - Level 1

Plan, Deploy, & Monitor Virtual Machines

By Idan Gabrieli | in Online Courses

Cloud computing is one of the biggest technology revolutions in the IT industry spreading at the speed of light all over the world. More and more business companies are looking for ways to migrate their applications into the cloud or to build new web-scale applications from scratch atop a cloud infrastructure. The demand for more skilled people in the area of cloud computing is increasing every day across multiple industries. This course is the first important cornerstone for learning how to migrate applications into the cloud while using the Infrastructure As a Service model inside Microsoft Azure.

  • Access 43 lectures & 5 hours of content 24/7
  • Understand the building blocks of Azure Infrastructure as a Service
  • Create virtual networks, subnets, allocate private & public IP addressees
  • Plan & deploy windows and Linux virtual machines
  • Configure traffic filtering using security rules
  • Manage & attach virtual disks to VMs
  • Create & manage storage accounts
  • Configure users & access role assignments
  • Operate & monitor VMs ongoing tasks

Instructor

Arduino Developers Academy (ADA) is an education program dedicated to Arduino developers and Internet of Things (IoT) makers who are keen on building cool electronics projects that combine low cost hardware components like sensors, LCDs, keyboards while using the Arduino development environment.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels

Requirements

  • Internet required

Course Outline

  • Getting Started
    • Welcome! - 2:19
    • Course Objectives and Structure - 3:24
  • Introduction to Microsoft Azure
    • Introduction to Microsoft Azure - 1:39
    • Cloud Computing Definition - 11:30
    • Microsoft Azure Cloud - 7:05
    • Global Footprint - 11:17
    • Demo - Azure Portal Overview - 15:55
    • Azure Resource Manager (ARM) - 13:03
    • Demo - Azure ARM - 12:35
    • Azure Role-Based Access Control (RBAC) - 6:05
    • Demo - Azure RBAC - 9:44
    • Test Your Knowledge - Introduction to Microsoft Azure
  • Azure IaaS - Networking
    • Section Overview - 2:22
    • What is a Virtual Network? - 7:13
    • Virtual Network Setting - 8:12
    • Demo - Creating a Virtual Network (VNet) - 4:55
    • IP Address Types - 6:42
    • VM, NICs and IP Configuration - 1:51
    • Demo - Network Interfaces and IP Configuration - 9:55
    • Network Security Group (NSG) - 7:14
    • Application Security Group (ASG) - 4:21
    • Demo - Configuring NSG and ASG - 16:48
    • Test Your Knowledge - Networking
  • Azure IaaS - Storage
    • Section Overview - 1:54
    • The Power of a Cloud Storage - 6:17
    • Types of Cloud Storage Services - 11:36
    • Azure Storage Services - 4:26
    • Storage Accounts - 6:53
    • Storage Replication Options - 7:48
    • Demo - Creating and Managing a Storage Account - 12:49
    • VMs Disks - 8:55
    • Demo - Create, Attach and Detach Data Disks - 14:23
    • Encryption Data at Rest - 9:59
    • Test Your Knowledge - Storage
  • Azure IaaS - Compute
    • Section Overview - 2:48
    • Virtualization - 5:23
    • Virtual Machines - 6:20
    • VM Types and Sizes - 4:20
    • Demo - Creating a VMs - 12:38
    • Demo - VMs Settings - 7:34
    • Demo - VMs Operations - 14:49
    • Demo - VMs Monitoring - 6:58
    • Test Your Knowledge - Compute
  • Mission is Possible! - Your Project Assignment
    • Mission Briefing - 1:17
    • Download Your Mission
  • Course Summary
    • Let's Summarize - 5:34
    • What Next? - 0:56

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2 hours
Lessons
41

Getting Started with Cloud Computing

Start Your Journey In the Cloud Computing Revolution

By Idan Gabrieli | in Online Courses

Cloud Computing is becoming mainstream in the IT world as a growing number of companies around the globe transform their use of cloud-based services. This evolution is leading to revolution as private as well as public cloud services gain huge market momentum and continue to innovate to make the spread of data more seamless. This entry-level course will get you up to speed with the cloud revolution and show you how to get involved.

  • Access 41 lectures & 2 hours of content 24/7
  • Explore the evolution of cloud technology
  • Discover the Five Characteristics of Cloud Computing
  • Discuss different cloud service models
  • Learn about different cloud deployment models

Instructor

Arduino Developers Academy (ADA) is an education program dedicated to Arduino developers and Internet of Things (IoT) makers who are keen on building cool electronics projects that combine low cost hardware components like sensors, LCDs, keyboards while using the Arduino development environment.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels

Requirements

  • Internet required

Course Outline

  • Getting Started
    • Course Introduction - 2:41
  • The Evolution into the Cloud Revolution
    • Overview - 1:05
    • Traditional IT - Plan, Buy and Operate the Data Center - 9:46
    • The First Wave started with SaaS - 3:57
    • The Digital Transformation - 8:58
    • The Birth of Hyper-scale Public Data Centers - 6:15
    • A Catalyst for Innovation - 4:26
    • The Rise of Artificial Intelligent - 2:52
  • The Five Characteristics of Cloud Computing
    • Overview - 1:55
    • #1 - On Demand Self-Service - 5:19
    • #2 - Broad Network Access - 1:55
    • #3 - Resource Pooling - 4:00
    • #4 - Rapid Elasticity - 6:33
    • #5 - Measured Service - 4:11
    • Five Characteristics of Cloud Computing - Quiz
  • Cloud Service Models
    • Overview - 2:25
    • The Cloud Computing Stack - 2:27
    • IaaS - Infrastructure as a Service - 4:17
    • PaaS - Platform as a Service - 3:56
    • SaaS - Software as a Service - 3:39
    • Cloud Service Models - Quiz
  • Cloud Deployment Models
    • Overview - 2:50
    • Public Cloud - Definition - 4:58
    • Public Cloud - Global Infrastructure - 2:34
    • Public Cloud - Products and Services - 9:49
    • Private Cloud - Definition - 3:55
    • Private Cloud - Key Benefits - 9:19
    • Hybrid Cloud - 4:22
    • Community Cloud - 1:41
    • Cloud Computing Management Platforms - 2:27
    • Cloud Deployment Models - Quiz
  • So, Why using a Public Cloud Service ?
    • Overview - 1:06
    • #1 - Easy and Dynamic Scalability - 2:01
    • #2 - Economies of Scale - 2:47
    • #3 - Capital and Operational Costs - 4:58
    • #4 - Increased Reliability - 1:53
    • #5 - Business Agility and Speed - 3:53
    • #6 - Yes, Security - 2:41
    • Benefits of Public Cloud Service - Quiz
  • Course Summary
    • Quick Recap - 10:36
    • What Next ? - 0:54

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6 hours
Lessons
69

Projects In Cloud Computing

Learn the Past, Present, & Future of This Lucrative Field

By Eduonix Learning Solutions | in Online Courses

Cloud computing is a shared platform where users can borrow storage, processing power and other services on demand, without having to physically add more systems to their current network. This drastically reduces the cost and offers better opportunities for companies, most commonly startups. With the huge number of apps and software that are in the market, cloud computing was definitely a needed option to reduce costs and help boost technological advancement. Cloud computing is the future of development and this one course covers a wide variety of cloud technologies and gives you the tools you need to build a career in this lucrative field.

  • Access 69 lectures & 6 hours of content 24/7
  • Explore cloud engineering techniques
  • Learn about the cloud architecture & different providers
  • Discuss application clients, build tools, design patterns, & programming languages
  • Discover emerging cloud technologies to keep an eye out for

Instructor

Eduonix creates and distributes high-quality technology training content. Their team of industry professionals has been training manpower for more than a decade. They aim to teach technology the way it is used in the industry and professional world. They have a professional team of trainers for technologies ranging from Mobility, Web and Enterprise, and Database and Server Administration.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner

Requirements

  • Internet required

Course Outline

  • Introduction
    • Intro - 3:54
  • Anatomy of an AWS Instance
    • Spin up a virtual machine (EC2) with security group - 5:49
    • Install Nginx - 4:55
    • Test Nginx as reverse proxy - 6:41
    • Extend Security with the IAM Console - 5:16
    • Ansible Configuration - 5:17
    • Provisioning with Ansible - 6:15
    • Setup Ansible Dynamic Inventory - 5:08
    • Use Dynamic Inventory - 7:14
    • Going Further with AWS - 6:05
  • Firebase
    • Setup a Firebase Development Environment - 5:48
    • Firebase Authentication - 6:09
    • Using Firebase Internal API’s Storage - 5:53
    • Using Firebase Internal API’s Database - 6:13
  • Cloud Programming Languages
    • Cloud Programming Languages - 6:30
  • Google Cloud Platform (gcloud) PAAS
    • Setup a Google Cloud Platform Development Environment - 5:59
    • Setup a Google Cloud Platform Shell Environment Part A - 6:05
    • Setup a Google Cloud Platform Shell Environment Part B - 5:36
    • Setup a Google Cloud App Engine Rest API - 6:05
    • Extending Google Cloud App Engine Rest API with the DataStore - 5:20
    • Setup a Google Cloud Platform Key Value Store A - 4:52
    • Setup a Google Cloud Platform Key Value Store B - 6:21
    • Setup a Google Cloud Platform Key Value Store C - 6:44
  • Google Cloud Platform APIs
    • Google Cloud Storage, Set up a Gcloud Development Environment - 6:34
    • Setup a Google Cloud Platform File Storage Application - 5:30
    • Gcloud File Storage Application OAuth Config and API Implementation - 6:55
  • Azure Cloud Model
    • Understanding the Azure Cloud Model - 4:26
    • Create and Configure an Active Directory to access Azure Resources - 5:34
    • Set Active Directory Permissions to access Azure Resources - 6:20
    • Setup a Azure Development Environment - 5:31
    • Test the Azure Development Environment with the default key store - 6:34
    • Test the Azure Development Environment with the Resource manager - 6:24
  • Azure sdk
    • Provisioning with the Azure sdk - 5:26
    • Accessing and configuring the Provisioned machine - 5:49
    • Configuring Azure Network access - 6:12
    • Azure Storage with the Azure Python sdk - 5:40
    • Blobservice and File Upload with the Azure sdk - 6:31
  • Azure NoSQL
    • Azure NoSQL service with the Azure sdk - 5:41
    • Set up an Azure DocumentDb Development Environment - 5:39
    • Create and run a Azure DocumentDb NoSQL Client - 5:34
    • Working with DocumentDb NoSQL Client - 7:04
  • Introduction to the Netflix OSS
    • Introduction to the Netflix OSS - 5:56
    • Design a Cloud Project Using Netflix OSS - 5:55
  • Service Discovery
    • Service Discovery Registry with Netflix OSS Eureka: dependencies - 6:04
    • Service Discovery with Netflix OSS Eureka: runtime artifacts - 5:37
    • Service Discovery with Netflix OSS Eureka: putting it all together - 6:22
  • Real Time Guarantee
    • Real Time Guarantee with Netflix OSS Hystrix: Configuration - 6:08
    • Real Time Guarantee with Netflix OSS Hystrix: Implementation - 5:33
    • Real Time Guarantee with Netflix OSS Hystrix: runtime - 6:08
    • Implement a Netflix OSS Rest client with Feign: Configuration - 6:39
    • Implement a Netflix OSS Rest client with Feign: runtime - 5:29
  • Netflix Universal JavaScript
    • Netflix Universal JavaScript - 5:16
    • Netflix Universal JavaScript: configuration - 5:35
    • Netflix Universal JavaScript: client implementation - 6:14
    • Netflix Universal JavaScript: server configuration - 5:49
    • Netflix Universal JavaScript: server implementation - 5:21
  • Heroku Conceptual Model
    • Basic Concepts - 5:39
    • Set up a heroku development environment(PostgreSQL) - 6:02
    • Set up a heroku development environment(Heroku toolbelt) - 5:34
  • SpringBoot on Heroku
    • Spin up a spring boot app on Heroku - 6:24
    • Spin up a spring boot app on Heroku: production - 6:08
  • React js on Heroku
    • Spin up a React js app on Heroku - 13:24
    • Spin up a React js app on Heroku: production - 6:09
  • OpenShift EcoSystem
    • OpenShift EcoSystem High Level Concepts - 6:24
  • OpenShift Origin
    • OpenShift Origin Online Spin up a CMS - 6:20
  • OpenShift Container Platform
    • Introduction to OpenShift Container Platform basic concepts - 5:44
    • Setup the OpenShift Container Platform as a private cloud - 6:45
  • Kubernetes
    • Kubernetes, Containers and Pods - 6:40
  • Summary
    • Summary - 4:14

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2 hours
Lessons
9

Learn Cloud Computing From Scratch

Get Up to Speed with the Most Modern Advances in Digital Infrastructure

By Eduonix Learning Solutions | in Online Courses

Cloud computing has revolutionized industry and changed the way businesses manage their digital infrastructure. As it relies on a massive sharing of resources across a network, the opportunities and challenges for developers and network administrators are growing rapidly. In this course, you'll go from cloud computing zero to hero as you use popular cloud technologies like Google Compute Engine, Amazon AWS, and Red Hat to build a holistic understanding. Soon enough, you'll be ready to cash in on the enormous cloud computing wave.

  • Access 9 lectures & 2 hours of content
  • Learn basic cloud concepts like SAAS, PAAS & IAAS
  • Understand Linux systems & their effects on cloud infrastructure
  • Discover virtualization technologies like virtual hardware platforms, storage devices & more
  • Learn to use popular cloud technologies that businesses value highly

Instructor

Eduonix creates and distributes high-quality technology training content. Their team of industry professionals has been training manpower for more than a decade. They aim to teach technology the way it is used in the industry and professional world. They have a professional team of trainers for technologies ranging from Mobility, Web and Enterprise, and Database and Server Administration.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels

Requirements

  • Internet required

Course Outline

  • Introduction
    • Introduction To Cloud Computing - 4:33
  • Introduction to the Cloud
    • Service models (SaaS) - 19:40
    • Linux and the Cloud Operating System - 21:53
  • Cloud Technology With Examples
    • (IaaS) (PaaS) on Amazon AWS EC2 - 19:21
    • (IaaS) (PaaS) Google Cloud Compute - 20:37
    • (IaaS) (PaaS) Red Hat Open Shift - 20:23
  • Virtualisation Expanded with examples
    • Virtualization Architecture - 14:19
    • Virtualization Examples - 22:08
  • Summary
    • Course Summary - 1:57

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3 hours
Lessons
15

Learn Cloud Computing with AWS

Set Up & Manage Your Web Infrastructure with Amazon’s Cloud Services

By Eduonix Learning Solutions | in Online Courses

Learn about this popular cloud and infrastructure service provided by Amazon through expert instruction and a series of practical examples. AWS has quickly become the go-to solution for building Web applications in the cloud, and this course is the perfect overview to get you started.

  • Access 15 lectures & 3 hours of content 24/7
  • Receive an AWS infrastructure overview
  • Study Amazon simple services for messaging & email
  • Learn to use Amazon’s DynamoDB
  • Understand how to use Amazon’s S3 for scalable storage
  • Use EC2 to scale your project
  • Become an AWS system administrator

Instructor

Eduonix creates and distributes high-quality technology training content. Their team of industry professionals has been training manpower for more than a decade. They aim to teach technology the way it is used in the industry and professional world. They have a professional team of trainers for technologies ranging from Mobility, Web and Enterprise, and Database and Server Administration.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels

Requirements

  • Internet required

Course Outline

  • Introduction
    • Introduction - 10:42
  • Introduction to AWS
    • AWS_Overview - 13:50
    • AWSOverviewP2 - 15:48
  • AWS System Administration
    • AWS System Administration - 16:09
    • Set up of the SDK - 14:43
  • AWS Infrastructure As A Service IAAS
    • EC2 Virtual Servers - 16:14
    • Security group, Key pair and setting up the first EC2 box - 16:09
  • AWS Platform As A Service PAAS
    • Set up a DynamoDB Service - 16:33
    • Set up a S3 Service - 14:50
  • AWS Network As A Service
    • AWS Cloudfront Application - 15:54
    • Load Balancing and Provisioning - 15:54
  • AWS Simple Services
    • Simple Services - 12:59
    • Simple Services Email Application - 13:48
    • Simple Services Queue Service Application - 11:13
  • Summary
    • Summary - 2:41

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11 hours
Lessons
97

Google Cloud Platform: Cloud Architecture Track

Lead Companies to the Cloud as a Google-Certified Architect

By Loonycorn | in Online Courses

More companies are heading to the Cloud, which means demand is high for experts versed in this revolutionary technology. The Google Cloud Platform is quickly emerging as one of the premier tools in the industry, and this course will walk you through concepts and elements key to getting certified, particularly for Google's Cloud Architect track.

  • Access 97 lectures & 11 hours of content 24/7
  • Sharpen your networking knowledge w/ instruction on Virtual Private Clouds, shared VPCs & more
  • Familiarize yourself w/ key elements of Google's Cloud Architect track
  • Explore security concepts, like identity & access management, identity-aware proxying, API Keys and more

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertises at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web and mobile
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels

Requirements

  • Internet required

Course Outline

  • You, This Course and Us
    • You, This Course and Us - 2:02
    • Course Materials
  • Introduction
    • Theory, Practice and Tests - 10:28
    • Lab: Setting Up A GCP Account - 6:59
    • Why Cloud? - 9:45
    • Hadoop and Distributed Computing - 9:03
    • On-premise, Colocation or Cloud? - 10:07
    • Introducing the Google Cloud Platform - 13:22
    • Lab: Using The Cloud Shell - 6:01
    • Important! Delete unused GCP projects/instances
    • Quiz 1 GCP Introduction
  • Compute
    • About this section
    • Compute Options - 9:18
    • Google Compute Engine (GCE) - 7:40
    • Lab: Creating a VM Instance - 5:59
    • More GCE - 8:14
    • Lab: Editing a VM Instance - 4:45
    • Lab: Creating a VM Instance Using The Command Line - 4:43
    • Lab: Creating And Attaching A Persistent Disk - 4:00
    • Google Container Engine - Kubernetes (GKE) - 10:35
    • More GKE - 9:56
    • Lab: Creating A Kubernetes Cluster And Deploying A Wordpress Container - 6:55
    • App Engine - 6:50
    • Contrasting App Engine, Compute Engine and Container Engine - 6:05
    • Lab: Deploy And Run An App Engine App - 7:29
    • Quiz 2 Compute
  • Storage
    • About this section
    • Storage Options - 9:50
    • Quick Take - 13:43
    • Cloud Storage - 10:39
    • Lab: Working With Cloud Storage Buckets - 5:25
    • Lab: Bucket And Object Permissions - 3:52
    • Lab: Life cycle Management On Buckets - 5:06
    • Lab: Running A Program On a VM Instance And Storing Results on Cloud Storage - 7:09
    • Transfer Service - 5:09
    • Lab: Migrating Data Using The Transfer Service - 5:32
    • Lab: Cloud Storage ACLs and API access with Service Account - 7:49
    • Lab: Cloud Storage Customer-Supplied Encryption Keys and Life-Cycle Management - 9:27
    • Lab: Cloud Storage Versioning, Directory Sync - 8:41
  • Virtual Machines and Images
    • About this section
    • Live Migration - 10:16
    • Machine Types and Billing - 9:20
    • Sustained Use and Committed Use Discounts - 7:03
    • Rightsizing Recommendations - 2:22
    • RAM Disk - 2:07
    • Images - 7:45
    • Startup Scripts And Baked Images - 7:31
  • VPCs and Interconnecting Networks
    • About this section
    • VPCs And Subnets - 11:14
    • Global VPCs, Regional Subnets - 11:19
    • IP Addresses - 11:39
    • Lab: Working with Static IP Addresses - 5:46
    • Routes - 7:36
    • Firewall Rules - 15:33
    • Lab: Working with Firewalls - 7:05
    • Lab: Working with Auto Mode and Custom Mode Networks - 19:32
    • Lab: Bastion Host - 7:10
    • Cloud VPN - 7:26
    • Lab: Working with Cloud VPN - 11:11
    • Cloud Router - 10:31
    • Lab: Using Cloud Routers for Dynamic Routing - 14:07
    • Dedicated Interconnect Direct and Carrier Peering - 8:10
    • Shared VPCs - 10:11
    • Lab: Shared VPCs - 6:17
    • VPC Network Peering - 10:10
    • Lab: VPC Peering - 7:16
    • Cloud DNS And Legacy Networks - 5:18
    • Quiz 4 Networking
  • Managed Instance Groups and Load Balancing
    • About this section
    • Managed and Unmanaged Instance Groups - 10:53
    • Types of Load Balancing - 5:46
    • Overview of HTTP(S) Load Balancing - 9:20
    • Forwarding Rules Target Proxy and Url Maps - 8:31
    • Backend Service and Backends - 9:28
    • Load Distribution and Firewall Rules - 4:28
    • Lab: HTTP(S) Load Balancing - 11:21
    • Lab: Content Based Load Balancing - 7:06
    • SSL Proxy and TCP Proxy Load Balancing - 5:05
    • Lab: SSL Proxy Load Balancing - 7:49
    • Network Load Balancing - 5:07
    • Internal Load Balancing - 7:16
    • Autoscalers - 11:51
    • Lab: Autoscaling with Managed Instance Groups - 12:22
  • Ops and Security
    • About this section
    • StackDriver - 12:10
    • StackDriver Logging - 7:41
    • Lab: Stackdriver Resource Monitoring - 8:12
    • Lab: Stackdriver Error Reporting and Debugging - 5:51
    • Cloud Deployment Manager - 6:07
    • Lab: Using Deployment Manager - 5:10
    • Lab: Deployment Manager and Stackdriver - 8:26
    • Cloud Endpoints - 3:49
    • Cloud IAM: User accounts, Service accounts, API Credentials - 9:03
    • Cloud IAM: Roles, Identity-Aware Proxy, Best Practices - 9:31
    • Lab: Cloud IAM - 11:57
    • Data Protection - 12:04
    • Quiz 5 Operations and Security

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28 hours
Lessons
233

GCP: Complete Google Data Engineer & Cloud Architect Guide

Discuss the Google Cloud for ML with TensorFlow & Big Data with Managed Hadoop

By Loonycorn | in Online Courses

The Google Cloud Platform is not the most popular cloud offering out there (hello AWS!) but it may be the best cloud offering for high-end machine learning applications. That's because TensorFlow, the extremely popular deep learning technology is also from Google. This comprehensive guide to TensorFlow and the Google Cloud Platform will help put you on certification track to become a Google Data Engineer or Cloud Architect.

  • Access 233 lectures & 28 hours of content 24/7
  • Cover the material you need to pass Google Data Engineer & Cloud Architect certification exams
  • Explore AppEngine, Kubernetes, & Compute Engine
  • Discuss Big Data & Managed Hadoop w/ Dataproc, Dataflow, BigTable, BigQuery, & more
  • Learn what neural networks & deep learning are, how neurons work, & how neural networks are trained
  • Understand DevOps principles like StackDrive logging, monitoring, & cloud deployment management
  • Discover security, networking, & Hadoop foundations

Instructor

Loonycorn is comprised of two individuals—Janani Ravi and Vitthal Srinivasan—who have honed their respective tech expertise at Google and Flipkart. The duo graduated from Stanford University and believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels

Requirements

  • Internet required

Course Outline

  • You, This Course and Us
    • You, This Course and Us - 2:02
    • Course Materials
  • Introduction
    • Theory, Practice and Tests - 10:28
    • Lab: Setting Up A GCP Account - 6:59
    • Why Cloud? - 9:45
    • Hadoop and Distributed Computing - 9:03
    • On-premise, Colocation or Cloud? - 10:07
    • Introducing the Google Cloud Platform - 13:22
    • Lab: Using The Cloud Shell - 6:01
    • Important! Delete unused GCP projects/instances
    • quiz 1 GCP Introduction
  • Compute
    • About this section
    • Compute Options - 9:18
    • Google Compute Engine (GCE) - 7:40
    • Lab: Creating a VM Instance - 5:59
    • More GCE - 8:14
    • Lab: Editing a VM Instance - 4:45
    • Lab: Creating a VM Instance Using The Command Line - 4:43
    • Lab: Creating And Attaching A Persistent Disk - 4:00
    • Google Container Engine - Kubernetes (GKE) - 10:35
    • More GKE - 9:56
    • Lab: Creating A Kubernetes Cluster And Deploying A Wordpress Container - 6:55
    • App Engine - 6:50
    • Contrasting App Engine, Compute Engine and Container Engine - 6:05
    • Lab: Deploy And Run An App Engine App - 7:29
    • Quiz 2 Compute
  • Storage
    • About this section
    • Storage Options - 9:50
    • Quick Take - 13:43
    • Cloud Storage - 10:39
    • Lab: Working With Cloud Storage Buckets - 5:25
    • Lab: Bucket And Object Permissions - 3:52
    • Lab: Life cycle Management On Buckets - 5:06
    • Lab: Running A Program On a VM Instance And Storing Results on Cloud Storage - 7:09
    • Transfer Service - 5:09
    • Lab: Migrating Data Using The Transfer Service - 5:32
    • Lab: Cloud Storage ACLs and API access with Service Account - 7:49
    • Lab: Cloud Storage Customer-Supplied Encryption Keys and Life-Cycle Management - 9:27
    • Lab: Cloud Storage Versioning, Directory Sync - 8:41
  • Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS
    • About this section
    • Cloud SQL - 7:42
    • Lab: Creating A Cloud SQL Instance - 7:54
    • Lab: Running Commands On Cloud SQL Instance - 6:31
    • Lab: Bulk Loading Data Into Cloud SQL Tables - 9:09
    • Cloud Spanner - 7:27
    • More Cloud Spanner - 9:20
    • Lab: Working With Cloud Spanner - 6:49
    • Important! Delete unused GCP projects/instances
  • Hadoop Pre-reqs and Context
    • Hadoop Pre-reqs and Context
  • BigTable ~ HBase = Columnar Store
    • About this section
    • BigTable Intro - 7:59
    • Columnar Store - 8:14
    • Denormalised - 9:04
    • Column Families - 8:12
    • BigTable Performance - 13:21
    • Lab: BigTable demo - 7:39
    • Important! Delete unused GCP projects/instances
  • Datastore ~ Document Database
    • About this section
    • Datastore - 14:12
    • Lab: Datastore demo - 6:42
    • Quiz 3 Datastore
  • BigQuery ~ Hive ~ OLAP
    • About this section
    • BigQuery Intro - 11:03
    • BigQuery Advanced - 9:59
    • Lab: Loading CSV Data Into Big Query - 9:03
    • Lab: Running Queries On Big Query - 5:26
    • Lab: Loading JSON Data With Nested Tables - 7:28
    • Lab: Public Datasets In Big Query - 8:16
    • Lab: Using Big Query Via The Command Line - 7:45
    • Lab: Aggregations And Conditionals In Aggregations - 9:51
    • Lab: Subqueries And Joins - 5:44
    • Lab: Regular Expressions In Legacy SQL - 5:36
    • Lab: Using The With Statement For SubQueries - 10:45
  • Dataflow ~ Apache Beam
    • About this section
    • Data Flow Intro - 11:06
    • Apache Beam - 3:42
    • Lab: Running A Python Data flow Program - 12:56
    • Lab: Running A Java Data flow Program - 13:42
    • Lab: Implementing Word Count In Dataflow Java - 11:17
    • Lab: Executing The Word Count Dataflow - 4:37
    • Lab: Executing MapReduce In Dataflow In Python - 9:50
    • Lab: Executing MapReduce In Dataflow In Java - 6:08
    • Lab: Dataflow With Big Query As Source And Side Inputs - 15:50
    • Lab: Dataflow With Big Query As Source And Side Inputs 2 - 6:28
  • Dataproc ~ Managed Hadoop
    • About this section
    • Data Proc - 8:30
    • Lab: Creating And Managing A Dataproc Cluster - 8:11
    • Lab: Creating A Firewall Rule To Access Dataproc - 8:25
    • Lab: Running A PySpark Job On Dataproc - 7:39
    • Lab: Running The PySpark REPL Shell And Pig Scripts On Dataproc - 8:44
    • Lab: Submitting A Spark Jar To Dataproc - 2:10
    • Lab: Working With Dataproc Using The Gcloud CLI - 8:19
  • Pub/Sub for Streaming
    • About this section
    • Pub Sub - 8:25
    • Lab: Working With Pubsub On The Command Line - 5:35
    • Lab: Working With PubSub Using The Web Console - 4:39
    • Lab: Setting Up A Pubsub Publisher Using The Python Library - 5:52
    • Lab: Setting Up A Pubsub Subscriber Using The Python Library - 4:08
    • Lab: Publishing Streaming Data Into Pubsub - 8:18
    • Lab: Reading Streaming Data From PubSub And Writing To BigQuery - 10:14
    • Lab: Executing A Pipeline To Read Streaming Data And Write To BigQuery - 5:54
    • Lab: Pubsub Source BigQuery Sink - 10:20
  • Datalab ~ Jupyter
    • About this section
    • Data Lab - 3:01
    • Lab: Creating And Working On A Datalab Instance - 4:01
    • Lab: Importing And Exporting Data Using Datalab - 12:14
    • Lab: Using The Charting API In Datalab - 6:43
  • TensorFlow and Machine Learning
    • About this section
    • Introducing Machine Learning - 8:06
    • Representation Learning - 10:29
    • NN Introduced - 7:37
    • Introducing TF - 7:18
    • Lab: Simple Math Operations - 8:46
    • Computation Graph - 10:19
    • Tensors - 9:04
    • Lab: Tensors - 5:03
    • Linear Regression Intro - 9:59
    • Placeholders and Variables - 8:46
    • Lab: Placeholders - 6:36
    • Lab: Variables - 7:49
    • Lab: Linear Regression with Made-up Data - 4:52
    • Image Processing - 8:07
    • Images As Tensors - 8:18
    • Lab: Reading and Working with Images - 8:05
    • Lab: Image Transformations - 6:37
    • Introducing MNIST - 4:15
    • K-Nearest Neigbors as Unsupervised Learning - 7:44
    • One-hot Notation and L1 Distance - 7:31
    • Steps in the K-Nearest-Neighbors Implementation - 9:34
    • Lab: K-Nearest-Neighbors - 14:14
    • Learning Algorithm - 11:00
    • Individual Neuron - 9:54
    • Learning Regression - 7:53
    • Learning XOR - 10:29
    • XOR Trained - 11:13
  • Regression in TensorFlow
    • About this section
    • Lab: Access Data from Yahoo Finance - 2:49
    • Non TensorFlow Regression - 8:07
    • Lab: Linear Regression - Setting Up a Baseline - 11:18
    • Gradient Descent - 9:58
    • Lab: Linear Regression - 14:42
    • Lab: Multiple Regression in TensorFlow - 9:15
    • Logistic Regression Introduced - 10:18
    • Linear Classification - 5:27
    • Lab: Logistic Regression - Setting Up a Baseline - 7:33
    • Logit - 8:35
    • Softmax - 11:57
    • Argmax - 12:15
    • Lab: Logistic Regression - 16:56
    • Estimators - 4:12
    • Lab: Linear Regression using Estimators - 7:49
    • Lab: Logistic Regression using Estimators - 4:54
  • Vision, Translate, NLP and Speech: Trained ML APIs
    • About this section
    • Lab: Taxicab Prediction - Setting up the dataset - 14:38
    • Lab: Taxicab Prediction - Training and Running the model - 11:22
    • Lab: The Vision, Translate, NLP and Speech API - 10:53
    • Lab: The Vision API for Label and Landmark Detection - 7:00
  • Virtual Machines and Images
    • About this section
    • Live Migration - 10:16
    • Machine Types and Billing - 9:20
    • Sustained Use and Committed Use Discounts - 7:03
    • Rightsizing Recommendations - 2:22
    • RAM Disk - 2:07
    • Images - 7:45
    • Startup Scripts And Baked Images - 7:31
  • VPCs and Interconnecting Networks
    • About this section
    • VPCs And Subnets - 11:14
    • Global VPCs, Regional Subnets - 11:19
    • IP Addresses - 11:39
    • Lab: Working with Static IP Addresses - 5:46
    • Routes - 7:36
    • Firewall Rules - 15:33
    • Lab: Working with Firewalls - 7:05
    • Lab: Working with Auto Mode and Custom Mode Networks - 19:32
    • Lab: Bastion Host - 7:10
    • Cloud VPN - 7:26
    • Lab: Working with Cloud VPN - 11:11
    • Cloud Router - 10:31
    • Lab: Using Cloud Routers for Dynamic Routing - 14:07
    • Dedicated Interconnect Direct and Carrier Peering - 8:10
    • Shared VPCs - 10:11
    • Lab: Shared VPCs - 6:17
    • VPC Network Peering - 10:10
    • Lab: VPC Peering - 7:16
    • Cloud DNS And Legacy Networks - 5:18
    • Quiz 4 Networking
  • Managed Instance Groups and Load Balancing
    • About this section
    • Managed and Unmanaged Instance Groups - 10:53
    • Types of Load Balancing - 5:46
    • Overview of HTTP(S) Load Balancing - 9:20
    • Forwarding Rules Target Proxy and Url Maps - 8:31
    • Backend Service and Backends - 9:28
    • Load Distribution and Firewall Rules - 4:28
    • Lab: HTTP(S) Load Balancing - 11:21
    • Lab: Content Based Load Balancing - 7:06
    • SSL Proxy and TCP Proxy Load Balancing - 5:05
    • Lab: SSL Proxy Load Balancing - 7:49
    • Network Load Balancing - 5:07
    • Internal Load Balancing - 7:16
    • Autoscalers - 11:51
    • Lab: Autoscaling with Managed Instance Groups - 12:22
  • Ops and Security
    • About this section
    • StackDriver - 12:10
    • StackDriver Logging - 7:41
    • Lab: Stackdriver Resource Monitoring - 8:12
    • Lab: Stackdriver Error Reporting and Debugging - 5:51
    • Cloud Deployment Manager - 6:07
    • Lab: Using Deployment Manager - 5:10
    • Lab: Deployment Manager and Stackdriver - 8:26
    • Cloud Endpoints - 3:49
    • Cloud IAM: User accounts, Service accounts, API Credentials - 9:03
    • Cloud IAM: Roles, Identity-Aware Proxy, Best Practices - 9:31
    • Data Protection - 12:04
    • Lab: Cloud IAM - 11:57
    • Quiz 5: Operations and Security
  • Appendix: Hadoop Ecosystem
    • Introducing the Hadoop Ecosystem - 1:35
    • Hadoop - 9:45
    • HDFS - 10:55
    • MapReduce - 10:34
    • Yarn - 5:29
    • Hive - 7:19
    • Hive v RDBMS - 7:10
    • HQL vs. SQL - 7:38
    • OLAP in Hive - 7:36
    • Windowing Hive - 8:22
    • Pig - 8:04
    • More Pig - 6:38
    • Spark - 8:56
    • More Spark - 11:45
    • Streams Intro - 7:44
    • Microbatches - 5:42
    • Window Types - 5:48
    • Quiz 6: Hadoop Ecosystem

View Full Curriculum


Access
Lifetime
Content
19 hours
Lessons
156

Google Cloud Platform: Data Engineering Track

Come to Grips with the Premier Platform for Machine Learning Applications

By Loonycorn | in Online Courses

There are plenty of options out there for cloud computing, but the Google Cloud Platform is king for high-end machine learning applications. This course looks at how Google Cloud can be used for machine learning along with TensorFlow and Hadoop, taking you through neural networks, stream processing, and more. Your foray into the world of data engineering starts here.

  • Access 156 lectures & 19 hours of content 24/7
  • Get an in-depth look at storage on the Google Cloud Platform
  • Discover what neural networks are, how neurons work & how neural networks are trained
  • Learn more about stream processing w/ Dataflow & Pub/Sub

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertises at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web and mobile
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels

Requirements

  • Internet required

Course Outline

  • You, This Course and Us
    • You, This Course and Us - 2:02
    • Course Materials
  • Introduction
    • Theory, Practice and Tests - 10:28
    • Lab: Setting Up A GCP Account - 6:59
    • Why Cloud? - 9:45
    • Hadoop and Distributed Computing - 9:03
    • On-premise, Colocation or Cloud? - 10:07
    • Introducing the Google Cloud Platform - 13:22
    • Lab: Using The Cloud Shell - 6:01
    • Important! Delete unused GCP projects/instances
    • Quiz 1 GCP Introduction
  • Storage
    • About this section
    • Storage Options - 9:50
    • Quick Take - 13:43
    • Cloud Storage - 10:39
    • Lab: Working With Cloud Storage Buckets - 5:25
    • Lab: Bucket And Object Permissions - 3:52
    • Lab: Life cycle Management On Buckets - 5:06
    • Lab: Running A Program On a VM Instance And Storing Results on Cloud Storage - 7:09
    • Transfer Service - 5:09
  • Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS
    • About this section
    • Cloud SQL - 7:42
    • Lab: Creating A Cloud SQL Instance - 7:54
    • Lab: Running Commands On Cloud SQL Instance - 6:31
    • Lab: Bulk Loading Data Into Cloud SQL Tables - 9:09
    • Cloud Spanner - 7:27
    • More Cloud Spanner - 9:20
    • Lab: Working With Cloud Spanner - 6:49
    • Important! Delete unused GCP projects/instances
  • Hadoop Pre-reqs and Context
    • Hadoop Pre-reqs and Context
  • BigTable ~ HBase = Columnar Store
    • About this section
    • BigTable Intro - 7:59
    • Columnar Store - 8:14
    • Denormalised - 9:04
    • Column Families - 8:12
    • BigTable Performance - 13:21
    • Lab: BigTable demo - 7:39
    • Important! Delete unused GCP projects/instances
  • Datastore ~ Document Database
    • About this section
    • Datastore - 14:12
    • Lab: Datastore demo - 6:42
    • Quiz 3 Datastore
  • BigQuery ~ Hive ~ OLAP
    • About this section
    • BigQuery Intro - 11:03
    • BigQuery Advanced - 9:59
    • Lab: Loading CSV Data Into Big Query - 9:03
    • Lab: Running Queries On Big Query - 5:26
    • Lab: Loading JSON Data With Nested Tables - 7:28
    • Lab: Public Datasets In Big Query - 8:16
    • Lab: Using Big Query Via The Command Line - 7:45
    • Lab: Aggregations And Conditionals In Aggregations - 9:51
    • Lab: Subqueries And Joins - 5:44
    • Lab: Regular Expressions In Legacy SQL - 5:36
    • Lab: Using The With Statement For SubQueries - 10:45
  • Dataflow ~ Apache Beam
    • About this section
    • Data Flow Intro - 11:06
    • Apache Beam - 3:42
    • Lab: Running A Python Data flow Program - 12:56
    • Lab: Running A Java Data flow Program - 13:42
    • Lab: Implementing Word Count In Dataflow Java - 11:17
    • Lab: Executing The Word Count Dataflow - 4:37
    • Lab: Executing MapReduce In Dataflow In Python - 9:50
    • Lab: Executing MapReduce In Dataflow In Java - 6:08
    • Lab: Dataflow With Big Query As Source And Side Inputs - 15:50
    • Lab: Dataflow With Big Query As Source And Side Inputs 2 - 6:28
  • Dataproc ~ Managed Hadoop
    • About this section
    • Data Proc - 8:30
    • Lab: Creating And Managing A Dataproc Cluster - 8:11
    • Lab: Creating A Firewall Rule To Access Dataproc - 8:25
    • Lab: Running A PySpark Job On Dataproc - 7:39
    • Lab: Running The PySpark REPL Shell And Pig Scripts On Dataproc - 8:44
    • Lab: Submitting A Spark Jar To Dataproc - 2:10
    • Lab: Working With Dataproc Using The Gcloud CLI - 8:19
  • Pub/Sub for Streaming
    • About this section
    • Pub Sub - 8:25
    • Lab: Working With Pubsub On The Command Line - 5:35
    • Lab: Working With PubSub Using The Web Console - 4:39
    • Lab: Setting Up A Pubsub Publisher Using The Python Library - 5:52
    • Lab: Setting Up A Pubsub Subscriber Using The Python Library - 4:08
    • Lab: Publishing Streaming Data Into Pubsub - 8:18
    • Lab: Reading Streaming Data From PubSub And Writing To BigQuery - 10:14
    • Lab: Executing A Pipeline To Read Streaming Data And Write To BigQuery - 5:54
    • Lab: Pubsub Source BigQuery Sink - 10:20
  • Datalab ~ Jupyter
    • About this section
    • Data Lab - 3:01
    • Lab: Creating And Working On A Datalab Instance - 10:29
    • Lab: Importing And Exporting Data Using Datalab - 12:14
    • Lab: Using The Charting API In Datalab - 6:43
  • TensorFlow and Machine Learning
    • About this section
    • Introducing Machine Learning - 8:06
    • Representation Learning - 10:29
    • NN Introduced - 7:37
    • Introducing TF - 7:18
    • Lab: Simple Math Operations - 8:46
    • Computation Graph - 10:19
    • Tensors - 9:04
    • Lab: Tensors - 5:03
    • Linear Regression Intro - 9:59
    • Placeholders and Variables - 8:46
    • Lab: Placeholders - 6:36
    • Lab: Variables - 7:49
    • Lab: Linear Regression with Made-up Data - 4:52
    • Image Processing - 8:07
    • Images As Tensors - 8:18
    • Lab: Reading and Working with Images - 8:05
    • Lab: Image Transformations - 6:37
    • Introducing MNIST - 4:15
    • K-Nearest Neigbors as Unsupervised Learning - 7:44
    • One-hot Notation and L1 Distance - 7:31
    • Steps in the K-Nearest-Neighbors Implementation - 9:34
    • Lab: K-Nearest-Neighbors - 14:14
    • Learning Algorithm - 11:00
    • Individual Neuron - 9:54
    • Learning Regression - 7:53
    • Learning XOR - 10:29
    • XOR Trained - 11:13
  • Regression in TensorFlow
    • About this section
    • Lab: Access Data from Yahoo Finance - 2:49
    • Non TensorFlow Regression - 8:07
    • Lab: Linear Regression - Setting Up a Baseline - 11:18
    • Gradient Descent - 9:58
    • Lab: Linear Regression - 14:42
    • Lab: Multiple Regression in TensorFlow - 9:15
    • Logistic Regression Introduced - 10:18
    • Linear Classification - 5:27
    • Lab: Logistic Regression - Setting Up a Baseline - 7:33
    • Logit - 8:35
    • Softmax - 11:57
    • Argmax - 12:15
    • Lab: Logistic Regression - 16:56
    • Estimators - 4:12
    • Lab: Linear Regression using Estimators - 7:49
    • Lab: Logistic Regression using Estimators - 4:54
  • Vision, Translate, NLP and Speech: Trained ML APIs
    • About this section
    • Lab: Taxicab Prediction - Setting up the dataset - 14:38
    • Lab: Taxicab Prediction - Training and Running the model - 11:22
    • Lab: The Vision, Translate, NLP and Speech API - 10:53
    • Lab: The Vision API for Label and Landmark Detection - 7:00
  • Appendix: Hadoop Ecosystem
    • Introducing the Hadoop Ecosystem - 1:35
    • Hadoop - 9:45
    • HDFS - 10:55
    • MapReduce - 10:34
    • Yarn - 5:29
    • Hive - 7:19
    • Hive v RDBMS - 7:10
    • HQL vs. SQL - 7:38
    • OLAP in Hive - 7:36
    • Windowing Hive - 8:22
    • Pig - 8:04
    • More Pig - 6:38
    • Spark - 8:56
    • More Spark - 11:45
    • Streams Intro - 7:44
    • Microbatches - 5:42
    • Window Types - 5:48
    • Quiz 6 Hadoop Ecosystem

View Full Curriculum



Terms

  • Unredeemed licenses can be returned for store credit within 15 days of purchase. Once your license is redeemed, all sales are final.