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AWS Data Analytics Certification Course Overview

This AWS Big Data certification training in Toronto will help you develop a level of expertise in the domain of cloud computing. You will have an in-depth knowledge of the domain of cloud computing while simultaneously being able to deploy its models by the time you have finished this AWS Big Data certification course in Toronto.

AWS Data Analytics Training Key Features

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  • 44 hours of Blended Learning
  • Real-life industry-based projects
  • 24/7 support with dedicated project mentoring sessions
  • Flexibility to choose classes
  • Dedicated mentoring session from our industry expert faculty members

Skills Covered

  • AWS Quicksight
  • Kinesis streams
  • AWS Lambda and Glue
  • s3 and DynamoDB
  • Redshift
  • Amazon RDS
  • Hive on EMR
  • HBase with EMR
  • AWS Aurora

Training Options

online Bootcamp

C$ 999

  • 90 days of flexible access to online classes
  • Lifetime access to high-quality, self-paced learning content designed by industry experts
  • 24x7 learner assistance and support
  • Classes starting in Toronto from:-
11th Nov: Weekend Class
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Corporate Training

Customized to your team's needs

  • Blended learning delivery model (self-paced e-learning and/or instructor-led options)
  • Course, category, and all-access pricing
  • Enterprise-class learning management system (LMS)
  • Enhanced reporting for individuals and teams
  • 24x7 teaching assistance and support

AWS Data Analytics Course Curriculum

Eligibility

Professionals with technology backgrounds seeking to grow lucrative careers in the field of Data Engineering are sure to benefit from this AWS Big Data certification training in Toronto.
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Pre-requisites

For candidates seeking to take part in this AWS Big Data certification course in Toronto, it is very helpful to have a prior grasp of the basic concepts of AWS, Big Data, and Hadoop.
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Course Content

  • Section 1 - Self-paced Curriculum

    Preview

    • Lesson 01: Introduction

      07:51Preview
      • 1.01 Course Overview
        02:53
      • 1.02 Introducing Hands - On Case Study: Cadabra. com
        03:11
      • 1.03 Cost of the Course and Amazon Web Services (AWS) Budget Setup
        01:47

    • Lesson 02: Domain 01 - Collection

      02:23:22Preview
      • 2.01 Collection Section Introduction
        01:29
      • 2.02 Amazon Kinesis Data Streams Overview
        06:53
      • 2.03 Kinesis Producers
        11:12
      • 2.04 Kinesis Consumers
        08:12
      • 2.05 Kinesis Enhanced Fan Out
        03:30
      • 2.06 Kinesis Scaling
        07:36
      • 2.07 Kinesis - Handling Duplicate Records
        03:32
      • 2.08 Kinesis Security
        01:15
      • 2.09 Kinesis Data Firehose
        08:17
      • 2.10 CloudWatch Subscription Filter with Kinesis
        02:56
      • 2.11 [Exercise] Kinesis Firehose - Part One
        05:32
      • 2.12 [Exercise] Kinesis Firehose - Part Two
        07:39
      • 2.13 [Exercise] Kinesis Firehose - Part Three
        09:27
      • 2.14 [Exercise] Amazon Kinesis Data Streams
        07:09
      • 2.15 Amazon Simple Queue Service (Amazon SQS) Overview
        06:59
      • 2.16 Kinesis Data Streams Versus Amazon Simple Queue Service (Amazon SQS)
        04:34
      • 2.17 Internet of Things (IoT) Overview
        09:27
      • 2.18 Internet of Things (IoT) Components Deep Dive
        07:12
      • 2.19 Amazon Web Services (AWS) Database Migration Service (DMS)
        06:56
      • 2.20 Amazon Web Services (AWS) Direct Connect
        03:35
      • 2.21 Amazon Web Services (AWS) Snow Family
        11:14
      • 2.22 Amazon MSK: Managed Streaming for Apache Kafka
        06:43
      • 2.23 Kinesis Versus MSK
        02:03

    • Lesson 03: Domain 02 - Storage

      02:23:33Preview
      • 3.01 Amazon Simple Storage Service (Amazon S Three) Overview
        03:25
      • 3.02 Amazon Simple Storage Service (Amazon S Three) Hands On
        03:51
      • 3.03 Amazon Simple Storage Service (Amazon S Three) Storage Classes
        09:44
      • 3.04 Amazon Simple Storage Service (Amazon S Three) Storage Classes Hands On
        03:14
      • 3.05 Amazon Simple Storage Service (Amazon S Three) Lifecycle Rules
        05:17
      • 3.06 Amazon Simple Storage Service (Amazon S Three) Lifecycle Rules Hands On
        03:02
      • 3.07 Amazon Simple Storage Service (Amazon S Three) Versioning
        01:09
      • 3.08 Amazon Simple Storage Service (Amazon S Three) Versioning Hands On
        05:28
      • 3.09 Amazon Simple Storage Service (Amazon S Three) Replication
        02:10
      • 3.10 Amazon Simple Storage Service (Amazon S Three) Replication Hands On
        06:17
      • 3.11 Amazon Simple Storage Service (Amazon S Three) Performance
        06:13
      • 3.12 Amazon Simple Storage Service (Amazon S Three) Encryption
        07:48
      • 3.13 Amazon Simple Storage Service (Amazon S Three) Encryption Hands On
        06:02
      • 3.14 Amazon Simple Storage Service (Amazon S Three) Security and Bucket Policies
        05:29
      • 3.15 Amazon Simple Storage Service (Amazon S Three) Security and Bucket Policies Hands On
        07:44
      • 3.16 Amazon Simple Storage Service (Amazon S Three) and Glacier Select
        01:48
      • 3.17 Amazon Simple Storage Service (Amazon S Three) Event Notifications
        01:42
      • 3.18 Amazon Simple Storage Service (Amazon S Three) Event Notifications Hands On
        05:15
      • 3.19 Amazon DynamoDB Overview
        06:31
      • 3.20 Amazon DynamoDB Provisioned Throughput
        09:05
      • 3.21 Amazon DynamoDB Partitions
        03:01
      • 3.22 Amazon DynamoDB APIs
        08:43
      • 3.23 Amazon DynamoDB Indexes: Local Secondary Index (LSI) and Global Secondary Index (GSI)
        04:36
      • 3.24 Amazon DynamoDB Accelerator (DAX)
        02:50
      • 3.25 Amazon DynamoDB Streams
        02:27
      • 3.26 Amazon DynamoDB Time to Live (TTL)
        04:04
      • 3.27 Amazon DynamoDB Security
        00:57
      • 3.28 Amazon DynamoDB - Storing Large Objects
        03:41
      • 3.29 [Exercise] Amazon DynamoDB
        09:56
      • 3.30 Amazon ElastiCache Overview
        02:04

    • Lesson 04: Domain 03 - Processing

      02:58:24Preview
      • 4.01 Section Introduction: Processing
        01:22
      • 4.02 What is AWS Lambda?
        04:49
      • 4.03 Lambda Integration - Part One
        05:25
      • 4.04 Lambda Integration - Part Two
        06:04
      • 4.05 Lambda Costs, Promises, and Anti - Patterns
        04:51
      • 4.06 [Exercise] AWS Lambda
        08:39
      • 4.07 What is Glue and Partitioning your Data Lake
        06:03
      • 4.08 Glue Hive and Extract Transform and Load (ETL)
        10:05
      • 4.09 Glue ETL: Developer Endpoints, Running ETL Jobs with Bookmarks
        03:45
      • 4.10 Glue Costs and Anti - Patterns
        03:02
      • 4.11 AWS Glue Studio
        05:28
      • 4.12 AWS Glue DataBrew
        08:48
      • 4.13 AWS Glue Elastic Views
        01:37
      • 4.14 AWS Lake Formation
        05:17
      • 4.15 Amazon Elastic MapReduce (EMR) Architecture and Usage
        08:39
      • 4.16 Amazon Elastic MapReduce (EMR) Amazon Web Services (AWS) Integration and Storage
        07:44
      • 4.17 Amazon Elastic MapReduce (EMR) Promises and Introduction to Hadoop
        08:08
      • 4.18 Introduction to Apache Spark
        08:53
      • 4.19 Spark Integration with Kinesis and Redshift
        03:46
      • 4.20 Hive on Amazon Elastic MapReduce (EMR)
        07:33
      • 4.21 Apache Pig on Amazon Elastic MapReduce (EMR)
        02:10
      • 4.22 Apache HBase on Amazon Elastic MapReduce (EMR)
        04:01
      • 4.23 Presto on Amazon Elastic MapReduce (EMR)
        02:59
      • 4.24 Apache Zeppelin and Amazon Elastic MapReduce (EMR) Notebooks
        04:34
      • 4.25 Hue Splunk and Flume
        04:05
      • 4.26 S ThreeDistCp and Other Services
        04:37
      • 4.27 Amazon Elastic MapReduce (EMR) Security and Instance Types
        05:50
      • 4.28 [Exercise] Elastic MapReduce - Part One
        10:28
      • 4.29 [Exercise] Elastic MapReduce - Part Two
        10:32
      • 4.30 Amazon Web Services (AWS) Data Pipeline
        05:15
      • 4.31 Amazon Web Services (AWS) Step Functions
        03:55

    • Lesson 05: Domain 04 - Analysis

      02:42:15Preview
      • 5.01 Section Introduction: Analysis
        01:17
      • 5.02 Introduction to Kinesis Analytics
        08:26
      • 5.03 Kinesis Analytics Costs and RANDOM CUT FOREST
        02:19
      • 5.04 [Exercise] Kinesis Analytics - Part One
        09:51
      • 5.05 [Exercise] Kinesis Analytics - Part Two
        09:58
      • 5.06 Introduction to Amazon Elasticsearch
        09:23
      • 5.07 Amazon Elasticsearch Service
        07:29
      • 5.08 Amazon Elasticsearch Service Performance
        01:27
      • 5.09 [Exercise] Amazon Elasticsearch Service
        22:22
      • 5.10 Introduction to Amazon Athena
        04:48
      • 5.11 Athena and Glue, Costs, and Security
        08:49
      • 5.12 Athena Performance
        01:52
      • 5.13 [Exercise] Amazon Web Services (AWS) Glue and Athena
        09:09
      • 5.14 Amazon Redshift Introduction and Architecture
        08:38
      • 5.15 Redshift Spectrum and Performance Tuning
        04:50
      • 5.16 Amazon Redshift Durability and Scaling
        03:33
      • 5.17 Amazon Redshift Distribution Styles
        02:52
      • 5.18 Amazon Redshift Sort Keys
        03:08
      • 5.19 Amazon Redshift Data Flows and the COPY Command
        07:37
      • 5.20 Amazon Redshift Integration/Workload Management (WLM)/Vacuum/Anti-Patterns
        10:49
      • 5.21 Amazon Redshift Resizing (Elastic vs. Classic) and new Redshift features in Two Thousand and Twenty
        03:41
      • 5.22 Amazon Redshift Security Concerns
        01:31
      • 5.23 [Exercise] Redshift Spectrum - Part One
        07:54
      • 5.24 [Exercise] Redshift Spectrum - Part Two
        06:24
      • 5.25 Amazon Relational Database Service (RDS) and Aurora
        04:08

    • Lesson 06: Domain 05 - Visualization

      37:56Preview
      • 6.01 Section Introduction: Visualization
        00:52
      • 6.02 Introduction to Amazon QuickSight
        07:03
      • 6.03 Amazon QuickSight Pricing and Dashboards
        04:33
      • 6.04 Choosing Visualization Types
        12:32
      • 6.05 [Exercise] Amazon QuickSight
        10:12
      • 6.06 Other Visualization Tools (HighCharts D Three and so on)
        02:44

    • Lesson 07: Domain 06 - Security

      01:10:26Preview
      • 7.01 Encryption Hundred and One
        03:59
      • 7.02 S Three Encryption (Reminder)
        07:48
      • 7.03 Amazon Web Services Key Management Service (AWS KMS) Overview
        06:03
      • 7.04 Amazon Web Services Key Management Service (AWS KMS) Key Rotation
        03:09
      • 7.05 Amazon Web Services (AWS) CloudHSM Overview
        02:24
      • 7.06 Amazon Web Services AWS Security Features Deep Dive - Part One
        05:48
      • 7.07 Amazon Web Services AWS Security Features Deep Dive - Part Two
        05:09
      • 7.08 Amazon Web Services AWS Security Features Deep Dive - Part Three
        08:37
      • 7.09 Amazon Web Services Security Token Service (AWS STS) and Cross - Account Access
        02:29
      • 7.10 Identity Federation
        09:45
      • 7.11 Policies - Advanced
        05:59
      • 7.12 Amazon Web Services (AWS) CloudTrail
        05:58
      • 7.13 Virtual Private Cloud (VPC) Endpoints
        03:18

    • Lesson 08: Everything Else

      15:30Preview
      • 8.01 Amazon Web Services (AWS) Service Integrations
        10:41
      • 8.02 Instance Types for Big Data
        02:45
      • 8.03 Amazon Elastic Compute Cloud (Amazon EC Two) for Big Data
        02:04

    • Lesson 09: Preparing for the Exam

      23:18Preview
      • 9.01 Exam Tips
        09:12
      • 9.02 State of Learning Checkpoint
        06:29
      • 9.03 Exam Walkthrough and Signup
        04:47
      • 9.04 Save Fifty percent on your AWS Exam Cost
        01:41
      • 9.05 Get an Extra Thirty Minutes on your AWS Exam - Non - Native English Speakers Only
        01:09

    • Lesson 10: Appendix - Machine Learning Topics for the Amazon Web Services AWS Certified Big Data Exam

      51:00Preview
      • 10.01 Machine Learning Hundred and One
        06:39
      • 10.02 Classification Models
        06:13
      • 10.03 Amazon Machine Learning Service
        05:54
      • 10.04 Amazon SageMaker
        07:39
      • 10.05 Deep Learning Hundred and One
        09:42
      • 10.06 [Exercise] Amazon Machine Learning - Part One
        08:29
      • 10.07 [Exercise] Amazon Machine Learning - Part Two
        06:24

    • Lesson 11: Wrapping Up

      01:22
      • 11.01 Congratulations Now make sure you are ready
        01:22

  • Section 2 - Live Virtual Class Curriculum

    Preview

    • Lesson 01 - Course Introduction

      • Overview of Big Data on Certification Course
      • Overview of the Certification
      • Overview of the Course

    • Lesson 02 - AWS in Big Data Introduction

      • Introduction to Cloud Computing
      • Cloud Computing Deployments Models
      • Types of Cloud Computing Services
      • AWS Fundamentals
      • AWS Cloud Architecture Design Principles
      • Databases in AWS
      • Data Warehousing in AWS
      • AWS Services
      • AWS Step Functions
      • SNS Message Creation using Step Functions
      • Key Takeaways
      • Deploy a Data Warehouse Using Amazon Redshift

    • Lesson 03 - Collection

      • AWS Big Data Collection Services
      • Fundamentals of Amazon Kinesis
      • Kinesis Data Analytics Services
      • Loading Data into Kinesis Stream
      • Assisted Practice: Loading Data into Amazon Storage
      • Kinesis Data Stream Concepts
      • AWS Services and Kinesis Data Stream
      • Amazon Kinesis Data Firehose
      • Assisted Practice: Transfer Data into Delivery Stream using Firehose
      • Assisted Practice: Transfer VPC Flow log to Splunk using Firehose
      • Assisted Practice: Data Streaming Using Amazon Kinesis and SQL
      • Data Transfer using AWS Lambda
      • Assisted Practice: Backing up data in Amazon S3 using AWS Lambda
      • Amazon SQS (Simple Queue Service)
      • IoT in AWS and Big Data
      • AWS IoT Greengrass
      • AWS Data Pipeline
      • Assisted Practice: Export MySQL Data to Amazon S3 Using AWS Data Pipeline
      • Key Takeaways
      • Streaming Data with Kinesis Data Analytics
      • Kinesis Data Firehose with Lambda and OpenSearch
      • Perform ETL using Kinesis Analytics SQL

    • Lesson 04 - Storage and Data Management

      • AWS Bigdata Storage services
      • Data lakes and Analytics
      • Data Management
      • Fundamentals of Amazon Glacier
      • NoSQL Databases
      • DynamoDB: Introduction
      • DynamoDB: Core Components
      • Assisted Practice: Perform operations on DynamoDB table
      • DynamoDB in AWS Eco-System
      • DynamoDB: Partitions
      • Data Distribution
      • DynamoDB: GSI and LSI
      • DynamoDB: Streams
      • DynamoDB: Architecture
      • Redshift Serverless
      • Amazon Redshift Machine Learning
      • Assisted Practice: Create a Global Table using DynamoDB
      • DynamoDB Performance: Deep Dive
      • Partition Key Selection
      • Snowball and AWS Big Data
      • Assisted Practice: Data Migration using AWS Snowball
      • AWS DMS
      • AWS Aurora in Big Data
      • Assisted Practice: Create and Modify Aurora DB Cluster
      • Assisted Practice: Execute Interactive SQL Queries in Athena
      • Key Takeaways
      • DynamoDB
      • Storing and Retrieving the Data from DynamoDB

    • Lesson 05 - Processing - I

      • AWS Bigdata Processing Services
      • Overview of Amazon Elastic MapReduce (EMR)
      • EMR Cluster Architecture
      • Apache Hadoop
      • Apache Hadoop Architecture
      • Storage Options
      • EMR Operations
      • AWS Cluster
      • Assisted Practice: Create a cluster in S3
      • Assisted Practice: Monitor a Cluster in S3
      • Using Hue with EMR
      • Assisted Practice: Launch HUE Web Interface on Amazon EMR
      • Set Up HUE for Lightweight Directory Access Protocol (LDAP)
      • Assisted Practice: Configure HUE for LDAP Users
      • Hive on EMR
      • Assisted Practice: Set Up a Hive Table to Run Hive Commands
      • Using HBase with HMR
      • Key Takeaways

    • Lesson 06 - Processing - II

      • Using HBase with EMR
      • HBase Architecture
      • Assisted Practice: Create a cluster with HBase
      • HBase and EMRFS
      • Presto with EMR
      • Presto Architecture
      • Fundamentals of Apache Spark
      • Apache Spark Architecture
      • Assisted Practice: Create a cluster with Spark
      • Apache Spark Integration with EMR
      • Fundamentals of EMR File System
      • Amazon Simple Workflow
      • AWS Lambda in Big Data Ecosystem
      • AWS Lambda and Kinesis Stream
      • AWS Lambda and RedShift
      • HCatalog
      • Key Takeaways
      • Real-Time Application with Apache Spark and AWS EMR

    • Lesson 07 - ETL with Redshift

      • Introduction to AWS Bigdata Analysis Services
      • Fundamentals of Amazon Redshift
      • Amazon RedShift Architecture
      • Assisted Practice: Launch a Cluster, Load Dataset, and Execute Queries
      • RedShift in the AWS Ecosystem
      • Columnar Databases
      • Assisted Practice: Monitor RedShift Maintenance and Operations
      • RedShift Table Design
      • Choosing the Distribution Style
      • Choosing the Sort Key
      • Redshift Data types
      • RedShift Data Loading
      • Assisted Practice: AWS Redshift Cluster Creation with Programming Language
      • COPY Command for Data Loading
      • Assisted Practice: Tuning Table Design
      • Key Takeaways

    • Lesson 08 - Analysis with Machine Learning

      • Fundamentals of Machine Learning
      • Workflow of Amazon Machine Learning
      • Use cases
      • Machine learning Algorithms
      • Amazon SageMaker
      • Machine learning with Amazon Sagemaker
      • Assisted Practice: Build, Train, and Deploy a Machine Learning Model
      • Elasticsearch
      • Amazon Elasticsearch Service
      • Zone Awareness
      • Logstash
      • RStudio
      • Assisted Practice: Fetch the File and Run Analysis using RStudio
      • Amazon Athena
      • Assisted Practice: Execute Interactive SQL Queries in Athena
      • AWS Glue Architecture
      • Overview of EL, ETL, and ELT
      • AWS Glue
      • AWS Glue Components
      • Assisted Practice: Create a database, Crawler, and S3 bucket resource to execute SQL query on Athena
      • Assisted Practice: Create an AWS Glue with S3 permissions for ETL operations
      • Lesson End Project : Glue-job
      • Fraud Detection Using Classification Algorithms on AWS Sagemaker
      • Key Takeaways

    • Lesson 09 - Analysis and Visualization

      • Introduction to AWS Bigdata Visualization Services
      • Amazon QuickSight
      • Amazon QuickSight - Workflow and Use Cases
      • Assisted Practice: Analyze the marketing campaign
      • Working with data
      • Assisted Practice: Analyze the marketing campaign using data from Amazon S3
      • Assisted Practice: Analyze the marketing campaign using data from Presto
      • Amazon QuickSight: Visualization
      • Assisted Practice: Create Visuals
      • Amazon QuickSight: Stories
      • Assisted Practice: Create a Storyboard
      • Amazon QuickSight: Dashboard
      • Assisted Practice: Create a Dashboard
      • Data Visualization: Other Tools
      • Kibana
      • Assisted Practice: Create a Dashboard on Kibana
      • Key Takeaways
      • Exploratory Data Analysis Using AWS QuickSight

    • Lesson 10 - Security

      • Introduction to AWS Bigdata Security
      • EMR Security
      • EMR Security: Best Practices
      • Roles
      • Fundamentals of Redshift Security
      • Data Protection and Encryption
      • Master Key, Encryption, and Decryption Process
      • Amazon Redshift Database Encryption
      • Key Management Services(KMS) Overview
      • Encryption using Hardware Security Modules(HSM)
      • Assisted Practice: Configure Hardware Security Model for Cloud
      • Security Token Service (STS) and Cross Account Access
      • AWS Cloud Trail
      • Assisted Practice: Create AWS CloudTrail
      • Key Takeaways

  • Practice Projects

    Preview

    • Practice Projects

      • Real-time Analytics on Streaming Data
      • Truegate S3 Replication Big Data Assignment
  • Free Course

  • AWS Technical Essentials

    Preview

    • Lesson 01: Introduction to AWS Cloud Practitioner Course

      29:16Preview
      • 1.01 AWS CP Introduction
        02:04
      • 1.02 Introduction to AWS Cloud Practitioner Course
        05:02
      • 1.03 Domain Introduction
        08:38
      • 1.04 AWS Certification Path
        08:44
      • 1.05 Exam Details
        04:48

    • Lesson 02: Core Concept of Cloud Computing

      01:32:45Preview
      • 2.01 Learning Objectives
        00:50
      • 2.02 Networking Terminologies Part 1
        08:14
      • 2.03 Networking Terminologies Part 2
        07:52
      • 2.04 Client Server Architecture
        07:30
      • 2.05 Classic Data Centres
        06:40
      • 2.06 Virtualization
        07:43
      • 2.07 Basics of Cloud Computing
        07:48
      • 2.08 Cloud Computing Deployment Models
        00:30
      • 2.09 Public Cloud
        06:56
      • 2.10 Private Cloud
        06:02
      • 2.11 Hybrid Cloud
        06:47
      • 2.12 Community Cloud
        02:30
      • 2.13 Comparison of Deployment Models
        03:54
      • 2.14 Cloud Computing Service Models Part 1
        09:02
      • 2.15 Cloud Computing Service Models Part 2
        03:09
      • 2.16 Pizza Analogy
        02:22
      • 2.17 Cloud Service Providers
        03:09
      • 2.18 Summary
        01:47

    • Lesson 03: Introduction to AWS

      04:25:50Preview
      • 3.01 Learning Objective
        00:32
      • 3.02 AWS Overview
        09:04
      • 3.03 Demo Setting Up AWS Account
        04:03
      • 3.04 Gartner Research
        01:59
      • 3.05 Cloud Architecture Design Principles
        04:34
      • 3.06 Well Architected Framework
        05:38
      • 3.07 Operational Excellence
        04:27
      • 3.08 Security
        05:34
      • 3.09 Reliability
        04:19
      • 3.10 Performance Efficiency
        04:11
      • 3.11 Cost Management
        03:17
      • 3.12 AZ and Regions
        10:07
      • 3.13 CloudFront Infrastructure
        03:01
      • 3.14 Edge Locations
        02:56
      • 3.15 Networking and Content Delivery Services
        00:54
      • 3.16 Virtual Private Cloud(VPC)
        15:26
      • 3.17 VPC Peering
        02:37
      • 3.18 VPC End Points
        01:18
      • 3.19 Domain Name System(DNS)
        01:47
      • 3.20 CDN
        04:15
      • 3.21 CloudFront Infrastructure
        02:36
      • 3.22 Elastic Load Balancer
        03:50
      • 3.23 ELB Types
        06:35
      • 3.24 Compute Services
        08:46
      • 3.25 What is EC2
        03:28
      • 3.26 EC2 Benefits and Features
        08:13
      • 3.27 EC2 Creation Steps
        02:42
      • 3.28 Amazon Machine Image(AMI)
        04:08
      • 3.29 EC2 Instance Types
        05:26
      • 3.30 EC2 Creation Steps(Continue)
        05:43
      • 3.31 Demo Launching EC2 Instance using AWS Console
        13:04
      • 3.32 AWS CLI
        01:40
      • 3.33 Demo Launch an EC2 Instance using AWS Command Line Interface
        11:44
      • 3.34 EC2 Auto Scaling
        05:02
      • 3.35 Elastic Beanstalk
        07:06
      • 3.36 AWS Storage Services
        02:39
      • 3.37 Amazon S3(Simple Storage Service)
        07:42
      • 3.38 S3 Policies
        02:47
      • 3.39 Demo Create S3 Bucket and Bucket Policies
        08:10
      • 3.40 Database Services
        01:44
      • 3.41 AWS Databases
        03:41
      • 3.42 Database Types
        02:47
      • 3.43 Relational Database Service(RDS)
        05:08
      • 3.44 Database Connection
        04:01
      • 3.45 Demo RDS Usage
        12:19
      • 3.46 Introduction to DynamoDB
        02:06
      • 3.47 Demo Managing AWS DynamoDB
        05:28
      • 3.48 Resource Groups and Tagging
        07:35
      • 3.49 Case Study
        04:32
      • 3.50 Demo Use of VPC and Subnet
        13:41
      • 3.51 Summary
        01:28

    • Lesson 04: AWS Security and Compliance

      01:49:32Preview
      • 4.01 Learning Objective
        00:37
      • 4.02 Security Aspects
        08:21
      • 4.03 Security and Compliance Principles
        07:56
      • 4.04 AWS Access Control and IAM
        10:10
      • 4.05 IAM Working
        04:38
      • 4.06 Security BestPractices Part 1
        08:36
      • 4.07 Security Best Practices Part 2
        07:50
      • 4.08 Web Application Firewall
        09:56
      • 4.09 AWS Shield
        06:17
      • 4.10 Firewall Manager
        03:38
      • 4.11 AWS CloudTrail
        05:42
      • 4.12 AWS CloudWatch
        07:29
      • 4.13 AWS Config Service
        03:46
      • 4.14 CloudWatch vs CloudTrail
        00:59
      • 4.15 AWS Config vs CloudTrail
        00:40
      • 4.16 AWS Inspector
        04:25
      • 4.17 AWS Trusted Advisor
        04:59
      • 4.18 Demo Managing IAM Service
        12:54
      • 4.19 Summary
        00:39

    • Lesson 05: AWS Costing and Support Service

      38:50Preview
      • 5.01 Learning Objective
        00:34
      • 5.02 Understand AWS Pricing
        05:22
      • 5.03 AWS Pricing Models
        07:37
      • 5.04 Cost Calculator
        07:51
      • 5.05 Support Plans
        06:44
      • 5.06 Marketplace
        05:17
      • 5.07 Demo Setup Billing Budget and Check Invoice
        04:01
      • 5.08 Summary
        01:24

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Industry Project

  • Project 1

    RealTime Analytics on Streaming Data with Amazon Kinesis and Amazon Elasticsearch Service

    Assist Facebook to do a continuous monitoring system to detect sentiment changes in a social media feed to react to the sentiment in near real time.

  • Project 2

    Real Time Analytics on Streaming Data

    Use the big data stack for data engineering to analyze a stream of data coming from IoT temperature sensor devices in real time.

  • Project 3

    Transactional Data Analysis

    Use the big data stack for data engineering for analysis of transactions, share patterns and actionable insights.

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AWS Data Analytics Exam & Certification

AWS Big Data Certification Training in Toronto

  • Who provides the certification for this course?

    The certification for the AWS Big Data certification training in Toronto is provided by Simplilearn. You can collect your certificate by completing the curriculum of the AWS Big Data certification training in Toronto.

  • How can I earn my Simplilearn Certificate for AWS?

    To receive the AWS Big Data certification training in Toronto certificate in the online classroom mode, a candidate needs to fulfill the following criteria:

    • 100% completion of the curriculum included in the AWS Big Data certification course in Toronto.
    • 80% score in at least one of the projects and simulation tests offered in the AWS Big Data certification course in Toronto.

  • How long does it take to complete the AWS Big Data certification course?

    It will take about 40-45 hours to successfully complete the AWS Big Data certification course.

  • How can I become an AWS Data Engineer?

    To become an AWS Big Data Engineer, you first need to pass the AWS Certified Data Analytics- Specialty Exam. You can appear for this exam after completing the AWS Big Data certification training in Toronto. The curriculum of the exam is covered in great detail in the AWS Big Data certification training in Toronto.

  • What is the duration of the AWS Big Data Certification Course?

    The duration of the AWS Big Data certification training in Toronto is around 40 to 45 hours. You can complete this AWS Big Data certification training in Toronto over a long period of time.

  • What is the period of validity of Simplilearn's AWS Big Data Certificate?

    Simplilearn's AWS Big Data certification training in Toronto comes with lifetime validity. You can use the AWS Big Data certification training in Toronto certification in your resume whenever you complete this course.

  • How much does the AWS Certified Data Analytics- Specialty Exam cost?

    Once you have completed your AWS Big Data certification training in Toronto, you will need to pay 300 US Dollars to apply for the AWS Certified Data Analytics- Specialty Exam. Upon clearing this exam, you can use your AWS Big Data certification training in Toronto certification to apply for jobs in the Big Data industry.

  • How long does it take to complete the AWS Data Analytics certification course?

    It will take about 40-45 hours to successfully complete the AWS Data Analytics certification  course.

Why Online Bootcamp

  • Develop skills for real career growthCutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills
  • Learn from experts active in their field, not out-of-touch trainersLeading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.
  • Learn by working on real-world problemsCapstone projects involving real world data sets with virtual labs for hands-on learning
  • Structured guidance ensuring learning never stops24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts

AWS Data Analytics Training FAQs

  • What is Big Data on AWS?

    Big Data on AWS is all about fitting AWS solutions inside a Big Data ecosystem. It includes knowledge of cloud-based Big data solutions such as Amazon EMR, Amazon Kinesis, Amazon Redshift, and Amazon Athena. Moreover, you’ll understand how to leverage best practices for designing Big Data environments for security, analysis, and cost-effectiveness.

  • How can beginners learn Big Data on AWS?

    Beginners who are interested to learn how to build Big Data solutions on AWS can get started by referring to project guides, tutorials, or guided labs offered by AWS. However, this AWS Big Data certification training in Toronto is curated for beginners, and enrolling in it can help you learn all the important concepts clearly.

  • Are the training and course material effective in preparing for the DAS-CO1 AWS Data Analytics -Speciality certification exam?

    Yes, the training and course material offered by Simplilearn is aligned with the exam changes introduced by AWS and assists you in preparing for the DAS-C01 exam.

  • What is included with the AWS Data Analytics certification training?

    You will get access to our e-learning content, practice simulation tests, and an online participant handbook that cross-references the e-learning to reinforce what you’ve learned.

  • How do I enroll for the AWS Big Data certification training in Toronto?

    You can enroll for this AWS Big Data certification training in Toronto on our website and make an online payment using any of the following options:

    • Visa Credit or Debit Card
    • MasterCard
    • American Express
    • Diner’s Club
    • PayPal 

    Once payment is received, you will automatically receive a payment receipt and access information via email.

  • What is the salary of an AWS big data engineer in Toronto?

    In Toronto, Ontario, the average compensation for an AWS big data engineer with AWS big data certification in Toronto is C$82881.

  • What are the major companies hiring AWS big data engineers in Toronto?

    Major organizations such as Rackspace, Cognizant technology solutions, Munich RE, Takeaway.com, Citi, AdGear are hiring AWS big data engineers with AWS big data certification, Toronto.

  • What are the major industries in Toronto?

    Canada is among the world's largest agricultural commodity providers. Canada sells the majority of its crops to its older brother to the south, America, due to its advantageous location. Canada has rapidly risen to prominence as a world leader in energy supplies due to its oil and natural gas availability. Canada not only possesses the world's third-largest reserves of oil, but it's also a global leader in hydroelectricity, with Quebec, Ontario, and Saskatchewan all relying heavily on it.

  • How to become an AWS big data engineer in Toronto?

    At the very least, an AWS certification at the entry-level is required to become an AWS big data engineer in Toronto. A few years of data analytics experience and AWS big data certification in Toronto are required. An in-depth understanding of Big Data's fundamentals, best practices, and guiding principles are also necessary.

  • How to Find AWS Big Data Certification in Toronto?

    You may look up AWS big data certification Toronto on the internet and compare various online training options based on the curriculum, industry partners, professors, accreditations, and other factors. You can make your final decision based on your schedule and budget limits. To acquire a better understanding of the course and make the selection process go more smoothly, you might also chat with industry experts or admission counselors from training providers.

  • What is online classroom training?

    Online classroom training for the AWS Data Analytics certification  course is conducted via online live streaming of each class. The classes are conducted by an AWS Data Analytics  certified trainer with more than 15 years of work and training experience.

  • What if I miss a class?

    Simplilearn provides recordings of each AWS Data Analytics training class so you can review them as needed before the next session. With Flexi-Pass, Simplilearn gives you access to all classes for 90 days so that you have the flexibility to choose sessions at your convenience.

  • Who are the instructors and how are they selected?

    All of our highly qualified AWS Data Analytics  trainers are industry experts with years of relevant industry experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.

  • What is Global Teaching Assistance?

    Our teaching assistants are a dedicated team of subject matter experts motivated to help you get certified on your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Global Teaching Assistance is available during regular business hours.

  • What is covered under the 24/7 Support Promise?

    We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you’ll have lifetime access to the community forum, even after you complete your course.

  • Who can I contact to learn more about this AWS Data Analytics course?

    Please contact us using the form on the right of any page on the Simplilearn website, or select the Live Chat link. Our customer service representatives will be able to give you more details.

  • Can I cancel my enrollment? Do I get a refund?

    Yes, you can cancel your enrollment. We provide a complete refund after deducting the administration fee. To know more, please go through our Refund Policy.

  • What is the recommended learning path after completing the AWS Data Analytics training course?

    You can either enroll in our Big Data Engineer certification training or if you are looking to get the University certificate, you can enroll in the Post Graduate Program in Data Engineering.

AWS Big Data Certification Training in Toronto

With a population of 2.9 million populace, Toronto is Canada's largest metropolis and North America's fifth most populated municipality. Over 6 million inhabitants live in the Greater Toronto region, sometimes known as the GTA. Toronto is located in the 'Golden Horseshoe' of Southern Ontario. Although its Great Lakes proximity helps soften the climate, Toronto's is more severe than Bordeaux's and Christchurch's, with slightly hotter summers and significantly colder winters. Toronto is Canada's financial and banking hub, as well as the location of the Toronto Stock Exchange, the country's primary stock exchange.

If you want to explore one of the most distinctive cities in North America, you must travel to Toronto, Canada. If you visit for a vacation or longer, you will discover a city rich in sports, gastronomy, and culture.

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  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.

This course has been upgraded to

Post Graduate Program in Data Engineering

  • Post Graduate Program Certificate and Alumni Association membership
  • Exclusive Master Classes and Ask me Anything sessions by IBM
  • Live sessions on the latest AI trends, such as generative AI, prompt engineering, explainable AI, and more