Who provides the certification for this course?

Simplilearn is the sponsor of the AWS Big Data certification training in Tampa. A candidate can unlock their certificate by completing the entire curriculum included in the AWS Big Data certification course in Tampa.

How can I earn my Simplilearn Certificate for AWS?

In the online classroom mode of AWS Big Data certification training in Tampa, you need to: Attend 100% of the classes in the AWS Big Data certification course in Tampa. Score at least 80% in one of the projects and simulation tests included in the AWS Big Data certification course in Tampa.

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?

By the time you are done with the AWS Big Data certification training in Tampa, you should have enough expertise to successfully clear the AWS Certified Data Analytics- Specialty Exam. Once you have cleared the exam, you can use your AWS Big Data certification training in Tampa certification to apply at different Big Data firms.

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

The AWS Big Data certification training in Tampa occupies approximately 40 to 45 hours in terms of total duration. There isn’t a strict deadline to finish this AWS Big Data certification training in Tampa.

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

Once you have successfully completed the AWS Big Data certification training in Tampa, the certificate can be used at any point during your life. Simplilearn offers lifetime validity on the AWS Big Data certification training in Tampa.

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

To apply for the AWS Certified Data Analytics- Specialty Exam after completing your AWS Big Data certification training in Tampa, you must spend 300 USD. On passing the test successfully, you will find your candidature to be eligible for applying to jobs in the Big Data market with your AWS Big Data certification training in Tampa certification.

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.

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 Tampa is curated for beginners, and enrolling in it can help you learn all the important concepts clearly.

AWS Big Data Certification Training in Tampa

520 Ratings

8909 Learners

For a candidate seeking to develop a successful career in the industries of AWS and Big Data Analytics, Simplilearn's AWS Big Data certification training in Tampa is of utmost benefit. This course has been painstakingly designed by scholars and pioneers in the industries of AWS and Big Data Analytics. By the time you have completed this AWS Big Data certification course in Tampa, you will be proficient enough to clear the AWS Certified Data Analytics- Specialty Examination.

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AWS Data Analytics Certification Course Overview

This AWS Big Data certification training in Tampa familiarizes you with the utilities of the AWS platform of AMazon, including AWS Big Data storage, machine learning algorithms, Kinesis analytics, and so on. This AWS Big Data certification course in Tampa is also designed to help you understand the processes of cloud technology.

Watch INTRO VIDEO

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

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

Aspiring Data Engineers who take part in this AWS Big Data certification training in Tampa are often seen to have prior experience in domains of technology.

Pre-requisites

If you are looking to participate in this AWS Big Data certification course in Tampa, you are required to have a fundamental understanding of the AWS platform and the Big Data concepts.

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
  15:30
  - 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
  01:22Preview
  - 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
  38:50
  - 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

Download Syllabus

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

Who provides the certification for this course?
Simplilearn is the sponsor of the AWS Big Data certification training in Tampa. A candidate can unlock their certificate by completing the entire curriculum included in the AWS Big Data certification course in Tampa.
How can I earn my Simplilearn Certificate for AWS?
In the online classroom mode of AWS Big Data certification training in Tampa, you need to:
- Attend 100% of the classes in the AWS Big Data certification course in Tampa.
- Score at least 80% in one of the projects and simulation tests included in the AWS Big Data certification course in Tampa.
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?
By the time you are done with the AWS Big Data certification training in Tampa, you should have enough expertise to successfully clear the AWS Certified Data Analytics- Specialty Exam. Once you have cleared the exam, you can use your AWS Big Data certification training in Tampa certification to apply at different Big Data firms.
What is the duration of the AWS Big Data Certification Course?
The AWS Big Data certification training in Tampa occupies approximately 40 to 45 hours in terms of total duration. There isn’t a strict deadline to finish this AWS Big Data certification training in Tampa.
What is the period of validity of Simplilearn's AWS Big Data Certificate?
Once you have successfully completed the AWS Big Data certification training in Tampa, the certificate can be used at any point during your life. Simplilearn offers lifetime validity on the AWS Big Data certification training in Tampa.
How much does the AWS Certified Data Analytics- Specialty Exam cost?
To apply for the AWS Certified Data Analytics- Specialty Exam after completing your AWS Big Data certification training in Tampa, you must spend 300 USD. On passing the test successfully, you will find your candidature to be eligible for applying to jobs in the Big Data market with your AWS Big Data certification training in Tampa certification.
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 Tampa 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 Tampa?
You can enroll for this AWS Big Data certification training in Tampa 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 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.

Our Tampa Correspondence / Mailing address

Simplilearn's AWS Big Data Certification Training in Tampa

7320 East Fletcher Avenue Tampa, Florida 33637 United States

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

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Post Graduate Program in Data Engineering

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AWS Big Data Certification Training in Tampa

World’s #1 Online Bootcamp

AWS Data Analytics Certification Course Overview

Skills Covered

Training Options

Corporate Training

AWS Data Analytics Course Curriculum

Eligibility

Pre-requisites

Course Content

Section 1 - Self-paced Curriculum

Lesson 01: Introduction

1.01 Course Overview

1.02 Introducing Hands - On Case Study: Cadabra. com

1.03 Cost of the Course and Amazon Web Services (AWS) Budget Setup

Lesson 02: Domain 01 - Collection

2.01 Collection Section Introduction

2.02 Amazon Kinesis Data Streams Overview

2.03 Kinesis Producers

2.04 Kinesis Consumers

2.05 Kinesis Enhanced Fan Out

2.06 Kinesis Scaling

2.07 Kinesis - Handling Duplicate Records

2.08 Kinesis Security

2.09 Kinesis Data Firehose

2.10 CloudWatch Subscription Filter with Kinesis

2.11 [Exercise] Kinesis Firehose - Part One

2.12 [Exercise] Kinesis Firehose - Part Two

2.13 [Exercise] Kinesis Firehose - Part Three

2.14 [Exercise] Amazon Kinesis Data Streams

2.15 Amazon Simple Queue Service (Amazon SQS) Overview

2.16 Kinesis Data Streams Versus Amazon Simple Queue Service (Amazon SQS)

2.17 Internet of Things (IoT) Overview

2.18 Internet of Things (IoT) Components Deep Dive

2.19 Amazon Web Services (AWS) Database Migration Service (DMS)

2.20 Amazon Web Services (AWS) Direct Connect

2.21 Amazon Web Services (AWS) Snow Family

2.22 Amazon MSK: Managed Streaming for Apache Kafka

2.23 Kinesis Versus MSK

Lesson 03: Domain 02 - Storage

3.01 Amazon Simple Storage Service (Amazon S Three) Overview

3.02 Amazon Simple Storage Service (Amazon S Three) Hands On

3.03 Amazon Simple Storage Service (Amazon S Three) Storage Classes

3.04 Amazon Simple Storage Service (Amazon S Three) Storage Classes Hands On

3.05 Amazon Simple Storage Service (Amazon S Three) Lifecycle Rules

3.06 Amazon Simple Storage Service (Amazon S Three) Lifecycle Rules Hands On

3.07 Amazon Simple Storage Service (Amazon S Three) Versioning

3.08 Amazon Simple Storage Service (Amazon S Three) Versioning Hands On

3.09 Amazon Simple Storage Service (Amazon S Three) Replication

3.10 Amazon Simple Storage Service (Amazon S Three) Replication Hands On

3.11 Amazon Simple Storage Service (Amazon S Three) Performance

3.12 Amazon Simple Storage Service (Amazon S Three) Encryption

3.13 Amazon Simple Storage Service (Amazon S Three) Encryption Hands On

3.14 Amazon Simple Storage Service (Amazon S Three) Security and Bucket Policies

3.15 Amazon Simple Storage Service (Amazon S Three) Security and Bucket Policies Hands On

3.16 Amazon Simple Storage Service (Amazon S Three) and Glacier Select

3.17 Amazon Simple Storage Service (Amazon S Three) Event Notifications

3.18 Amazon Simple Storage Service (Amazon S Three) Event Notifications Hands On

3.19 Amazon DynamoDB Overview

3.20 Amazon DynamoDB Provisioned Throughput

3.21 Amazon DynamoDB Partitions

3.22 Amazon DynamoDB APIs

3.23 Amazon DynamoDB Indexes: Local Secondary Index (LSI) and Global Secondary Index (GSI)

3.24 Amazon DynamoDB Accelerator (DAX)

3.25 Amazon DynamoDB Streams

3.26 Amazon DynamoDB Time to Live (TTL)

3.27 Amazon DynamoDB Security

3.28 Amazon DynamoDB - Storing Large Objects

3.29 [Exercise] Amazon DynamoDB

3.30 Amazon ElastiCache Overview

Lesson 04: Domain 03 - Processing

4.01 Section Introduction: Processing

4.02 What is AWS Lambda?

4.03 Lambda Integration - Part One

4.04 Lambda Integration - Part Two

4.05 Lambda Costs, Promises, and Anti - Patterns

4.06 [Exercise] AWS Lambda

4.07 What is Glue and Partitioning your Data Lake

4.08 Glue Hive and Extract Transform and Load (ETL)

4.09 Glue ETL: Developer Endpoints, Running ETL Jobs with Bookmarks