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AWS Big Data Certification Training Course

Course Description

AWS Big Data Certification Training Course

The AWS Big Data certification training prepares you for all aspects of hosting big data and performing distributed processing on the AWS platform and has been aligned to the AWS Certified Data Analytics – Specialty exam. This course is developed by industry leaders and aligned with the latest best practices.

AWS Big Data Certification Course Overview

In this AWS Big Data certification course, you will become familiar with the concepts of cloud computing and its deployment models. This course covers Amazon’s AWS cloud platform, Kinesis Analytics, AWS big data storage, processing, analysis, visualization and security services, machine learning algorithms and much more.


This AWS Big Data certification course is well-suited for experienced technology professionals who want to excel in the data engineering space.


Participants in this AWS Big Data certification course should have basic knowledge of AWS technical essentials and a fair understanding of big data and Hadoop concepts.

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Course Syllabus

Lesson 1 Big Data on AWS Certification Course Overview

Overview of Big Data on AWS Certification Course
2.Course Introduction

Lesson 2 – Big Data on AWS Introduction

1. Learning Objective
2.Cloud computing and it’s advantages
3.Cloud Computing Models
4.Cloud Service Categories
5. AWS Cloud Platform
6.Design Principles – Part One
7. Design Principles – Part Two
8.Why AWS for Big Data – Reasons and Challenges
9.Databases in AWS
10.Data Warehousing in AWS
11.Redshift, Kinesis and EMR
12.DynamoDB, Machine Learning and Lambda
13.Elastic Search Services and EC2
14.Key Takeaways

Lesson 3 – AWS Big Data Collection Services

1.Learning Objective
2.Amazon Kinesis and Kinesis Stream
3.Kinesis Data Stream Architecture and Core Components
4.Data Producer
5.Data Consumer
6.Kinesis Stream Emitting Data to AWS Services and Kinesis Connector Library
7.Kinesis Firehose
8.Transferring Data Using Lambda
9.Amazon SQS, Lifecycle and Architecture
10.IoT and Big Data
11.IoT Framework
12.AWS Data Pipelines and Data Nodes
13.Activity, Pre-condition and Schedule
14Key Takeaways

Lesson 4 – AWS Big Data Storage Services

1.Learning Objective
2.Amazon Glacier and Big Data
3.DynamoDB Introduction
4.DynamoDB and EMR
5.DynamoDB Partitions and Distributions
6.DynamoDB GSI LSI
7.DynamoDB Stream and Cross Region Replication
8.DynamoDB Performance and Partition Key Selection
9.Snowball and AWS Big Data
11.AWS Aurora in Big Data
12.Demo – Amazon Athena Interactive SQL Queries for Data in Amazon S3 – Part 2
13.Key Takeaways

Lesson 5 – AWS Big Data Processing Services

1.Learning Objective
2.Amazon EMR
3.Apache Hadoop
4.EMR Architecture
5.EMR Releases and Cluster
6.Choosing Instance and Monitoring
7.Demo – Advance EMR Setting Options
8.Hive on EMR
9.HBase with EMR
10.Presto with EMR
11.Spark with EMR
12.EMR File Storage
13.AWS Lambda
14.Key Takeaways

Lesson 6 – Analysis

1.Learning Objective
2.Redshift Intro and Use cases
3.Redshift Architecture
4.MPP and Redshift in AWS Eco-System
5.Columnar Databases
6.Redshift Table Design – Part 2
7.Demo – Redshift Maintenance and Operations
8.Machine Learning Introduction
9.Machine Learning Algorithm
10.Amazon SageMaker
11.Amazon Elasticsearch
12.Amazon Elasticsearch Services
13.Demo – Loading Dataset into Elasticsearch
14.Logstash and R Studio
15.Demo – Fetching the File and Analyzing it using RStudio
17.Demo – Running Query on S3 using the Serverless Athena
18.Key Takeaways

Lesson 7 – Visualization

1.Learning Objective
2. Introduction to Amazon QuickSight
3.Visual Types
5.Big Data Visualization
6.Key Takeaways

Lesson 8 – Security

1.Learning Objective
2.EMR Security and Security Group
3.Roles and Private Subnet
4.Encryption at Rest and In-transit
5.Redshift Security
6.Encryption at Rest using HSM
7.Cloud HSM vs AWS KMS
8.Limit Data Access
9.Key Takeaways


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You Will Get Certification After Completetion This Course.

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Frequently Asked Questions

How does online education work on a day-to-day basis?
Instructional methods, course requirements, and learning technologies can vary significantly from one online program to the next, but the vast bulk of them use a learning management system (LMS) to deliver lectures and materials, monitor student progress, assess comprehension, and accept student work. LMS providers design these platforms to accommodate a multitude of instructor needs and preferences.
Is online education as effective as face-to-face instruction?
Online education may seem relatively new, but years of research suggests it can be just as effective as traditional coursework, and often more so. According to a U.S. Department of Education analysis of more than 1,000 learning studies, online students tend to outperform classroom-based students across most disciplines and demographics. Another major review published the same year found that online students had the advantage 70 percent of the time, a gap authors projected would only widen as programs and technologies evolve.
Do employers accept online degrees?
All new learning innovations are met with some degree of scrutiny, but skepticism subsides as methods become more mainstream. Such is the case for online learning. Studies indicate employers who are familiar with online degrees tend to view them more favorably, and more employers are acquainted with them than ever before. The majority of colleges now offer online degrees, including most public, not-for-profit, and Ivy League universities. Online learning is also increasingly prevalent in the workplace as more companies invest in web-based employee training and development programs.
Is online education more conducive to cheating?
The concern that online students cheat more than traditional students is perhaps misplaced. When researchers at Marshall University conducted a study to measure the prevalence of cheating in online and classroom-based courses, they concluded, “Somewhat surprisingly, the results showed higher rates of academic dishonesty in live courses.” The authors suggest the social familiarity of students in a classroom setting may lessen their sense of moral obligation.
How do I know if online education is right for me?
Choosing the right course takes time and careful research no matter how one intends to study. Learning styles, goals, and programs always vary, but students considering online courses must consider technical skills, ability to self-motivate, and other factors specific to the medium. Online course demos and trials can also be helpful.
What technical skills do online students need?
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