AWS Data Analytics Certification Training Course

BY
Simplilearn

Join AWS Big Data Certification training course by Simplilearrn to understand aspects of big data hosting and performing distributed processing on AWS platform.

Mode

Online

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video and Text Based

Course overview

The AWS Data Analytics Certification Training Course covers topics like Kinesis streams, AWS big data storage, processing, analysis, s3, DynamoDB, and security services. The AWS Big Data Certification course includes essential AWS methodologies and techniques, enabling students to get industry-ready and land a coveted job of their choice.

The course also offers a lot of hands-on experience, with many practice and industry-based projects for the students to dabble in. The projects also help candidates get a clear picture of what’s expected in the industry. Moreover, AWS Data Analytics Certification Training Course by Simplilearn will also enable candidates to prepare for the AWS Certified Data Analytics - Specialty exam.

Moreover, AWS Data Analytics Certification Training Course by Simplilearn also aims to provide the candidates with exhaustive knowledge about various elements of cloud computing and its deployment tactics via eLearning content, practice simulation tests, and industry-based projects. Candidates also receive 24x7 learner assistance for any queries. Upon course completion, successful candidates will receive a course completion certificate.

The highlights

  • 40 hours of Blended Learning
  • Interactive learning with Jupyter notebooks integrated labs
  • Dedicated mentoring session from the industry expert 
  • Industry-based projects

Program offerings

  • Blended learning
  • Corporate training
  • Industry case studies
  • Jupyter notebooks integrated labs
  • Dedicated monitoring sessions

Course and certificate fees

certificate availability

Yes

certificate providing authority

Simplilearn

Who it is for

The AWS Big Data certification course by Simplilearn is well-suited for those looking to widen their expertise in the field of big data. Some common profiles include

  • Data analysts
  • Solutions architects
  • Data engineers
  • Data scientists

Eligibility criteria

Skills

AWS Big Data certification course online requires a basic understanding about AWS technical essentials along with the intermediate knowledge of Big Data and Hadoop concepts.

Certification Qualifying Detail

Only those candidates will be able to qualify for the AWS Big Data Certification Training Course by Simplilearn who will attend one complete batch and also complete one simulation test and a project with at least 80% marks. 

What you will learn

Knowledge of big data Knowledge of aws technology
  • Gain an in-depth understanding of Amazon Quicksight and use it for Data visualisation and performing queries
  • Perform real-time Data processing using Amazon Kinesis. 
  • Deep-dive into Kinesis’ DataStream structure, its core constituents, and Kinesis Firehose
  • Gain familiarity with Lambda, Amazon web services’ event-driven, serverless computing platform.
  • Learn about Amazon Glue, AWS’s ETL service designed for data analytics
  • Use DynamoDB Amazon web services’ proprietary NoSQL Database service 
  • Acquire a fair understanding of Amazon s3, which provides a simple storage service through a web interface
  • Acquire a working knowledge of Amazon relational database services, or Amazon RDS, a distributed relational database service hosted by Amazon web services
  • Learn about Redshift is AWS’s proprietary Data warehousing service, based in the cloud. 
  • Use the platform to gain new insights into your data, which can prove to be beneficial to businesses and customers
  • Build proficiency in AWS Aurora another relational database system, belonging to AWS.

The syllabus

Session 1: Self-paced Curriculum

Lesson 1: Introduction
  • Course Overview
  • Introducing Hands - On Case Study: Cadabra. com 
  •  Cost of the Course and Amazon Web Services (AWS) Budget   
Lesson 2: Collection
  • Collection Section Introduction
  • Amazon Kinesis Data Streams Overview
  • Kinesis Producers
  • Kinesis Consumers
  • Kinesis Enhanced Fan Out
  • Kinesis Scaling
  • Kinesis - Handling Duplicate Records
  • Kinesis Security
  • Kinesis Data Firehose
  • CloudWatch Subscription Filter with Kinesis
  • [Exercise] Kinesis Firehose - Part One
  • [Exercise] Kinesis Firehose - Part Two
  • [Exercise] Kinesis Firehose - Part Three
  • [Exercise] Amazon Kinesis Data Streams
  • Amazon Simple Queue Service (Amazon SQS) Overview
  • Kinesis Data Streams Versus Amazon Simple Queue Service (Amazon SQS)
  • Internet of Things (IoT) Overview
  • Internet of Things (IoT) Components Deep Dive
  • Amazon Web Services (AWS) Database Migration Service (DMS)
  • Amazon Web Services (AWS) Direct Connect
  • Amazon Web Services (AWS) Snow Family
  • Amazon MSK: Managed Streaming for Apache Kafka
  • Kinesis Versus MSK
Lesson 3: Storage
  • Amazon Simple Storage Service (Amazon S Three) Overview
  • Amazon Simple Storage Service (Amazon S Three) Hands On
  • Amazon Simple Storage Service (Amazon S Three) Storage Classes
  • Amazon Simple Storage Service (Amazon S Three) Storage Classes Hands On
  • Amazon Simple Storage Service (Amazon S Three) Lifecycle Rules
  • Amazon Simple Storage Service (Amazon S Three) Lifecycle Rules Hands On
  • Amazon Simple Storage Service (Amazon S Three) Versioning
  • Amazon Simple Storage Service (Amazon S Three) Versioning Hands On
  • Amazon Simple Storage Service (Amazon S Three) Replication
  • Amazon Simple Storage Service (Amazon S Three) Replication Hands On
  • Amazon Simple Storage Service (Amazon S Three) Performance
  • Amazon Simple Storage Service (Amazon S Three) Encryption
  • Amazon Simple Storage Service (Amazon S Three) Encryption Hands On
  • Amazon Simple Storage Service (Amazon S Three) Security and Bucket Policies
  • Amazon Simple Storage Service (Amazon S Three) Security and Bucket Policies Hands On
  • Amazon Simple Storage Service (Amazon S Three) and Glacier Select
  • Amazon Simple Storage Service (Amazon S Three) Event Notifications
  • Amazon Simple Storage Service (Amazon S Three) Event Notifications Hands On
  • Amazon DynamoDB Overview
  • Amazon DynamoDB Provisioned Throughput
  • Amazon DynamoDB Partitions
  • Amazon DynamoDB APIs
  • Amazon DynamoDB Indexes: Local Secondary Index (LSI) and Global Secondary Index (GSI)
  • Amazon DynamoDB Accelerator (DAX)
  • Amazon DynamoDB Streams
  • Amazon DynamoDB Time to Live (TTL)
  • Amazon DynamoDB Security
  • Amazon DynamoDB - Storing Large Objects
  • [Exercise] Amazon DynamoDB
  • Amazon ElastiCache Overview
Lession 4: Processing
  • Section Introduction: Processing
  • What is AWS Lambda?
  • Lambda Integration - Part One
  • Lambda Integration - Part Two
  • Lambda Costs, Promises, and Anti - Patterns
  • [Exercise] AWS Lambda
  • What is Glue and Partitioning your Data Lake
  • Glue Hive and Extract Transform and Load (ETL)
  • Glue ETL: Developer Endpoints, Running ETL Jobs with Bookmarks
  • Glue Costs and Anti - Patterns
  • AWS Glue Studio
  • AWS Glue DataBrew
  • AWS Glue Elastic Views
  • AWS Lake Formation
  • Amazon Elastic MapReduce (EMR) Architecture and Usage
  • Amazon Elastic MapReduce (EMR) Amazon Web Services (AWS) Integration and Storage
  • Amazon Elastic MapReduce (EMR) Promises and Introduction to Hadoop
  • Introduction to Apache Spark
  • Spark Integration with Kinesis and Redshift
  • Hive on Amazon Elastic MapReduce (EMR)
  • Apache Pig on Amazon Elastic MapReduce (EMR)
  • Apache HBase on Amazon Elastic MapReduce (EMR)
  • Presto on Amazon Elastic MapReduce (EMR)
  • Apache Zeppelin and Amazon Elastic MapReduce (EMR) Notebooks
  • Hue Splunk and Flume
  • S ThreeDistCp and Other Services
  • Amazon Elastic MapReduce (EMR) Security and Instance Types
  • [Exercise] Elastic MapReduce - Part One
  • [Exercise] Elastic MapReduce - Part Two
  • Amazon Web Services (AWS) Data Pipeline
  • Amazon Web Services (AWS) Step Functions
Lesson 5: Analysis
  • Section Introduction: Analysis
  • Introduction to Kinesis Analytics
  • Kinesis Analytics Costs and RANDOM CUT FOREST
  • [Exercise] Kinesis Analytics - Part One
  • [Exercise] Kinesis Analytics - Part Two
  • Introduction to Amazon Elasticsearch
  • Amazon Elasticsearch Service
  • Amazon Elasticsearch Service Performance
  • [Exercise] Amazon Elasticsearch Service
  • Introduction to Amazon Athena
  • Athena and Glue, Costs, and Security
  • Athena Performance
  • [Exercise] Amazon Web Services (AWS) Glue and Athena
  • Amazon Redshift Introduction and Architecture
  • Redshift Spectrum and Performance Tuning
  • Amazon Redshift Durability and Scaling
  • Amazon Redshift Distribution Styles
  • Amazon Redshift Sort Keys
  • Amazon Redshift Data Flows and the COPY Command
  • Amazon Redshift Integration/Workload Management (WLM)/Vacuum/Anti-Patterns
  • Amazon Redshift Resizing (Elastic vs. Classic) and new Redshift features in Two Thousand and Twenty
  • Amazon Redshift Security Concerns
  • [Exercise] Redshift Spectrum - Part One
  •  [Exercise] Redshift Spectrum - Part Two
  • Amazon Relational Database Service (RDS) and Aurora
Lession 6: Visualization
  • Section Introduction: Visualization
  • Introduction to Amazon QuickSight
  • Amazon QuickSight Pricing and Dashboards
  • Choosing Visualization Types
  • [Exercise] Amazon QuickSight
  • Other Visualization Tools (HighCharts D Three and so on)
Lession 7: Security
  • Encryption Hundred and One
  • S Three Encryption (Reminder)
  • Amazon Web Services Key Management Service (AWS KMS) Overview
  • Amazon Web Services Key Management Service (AWS KMS) Key Rotation
  • Amazon Web Services (AWS) CloudHSM Overview
  • Amazon Web Services AWS Security Features Deep Dive - Part One
  • Amazon Web Services AWS Security Features Deep Dive - Part Two
  • Amazon Web Services AWS Security Features Deep Dive - Part Three
  • Amazon Web Services Security Token Service (AWS STS) and Cross - Account Access
  • Identity Federation
  • Policies - Advanced
  • Amazon Web Services (AWS) CloudTrail
  • Virtual Private Cloud (VPC) Endpoints
Lession 8: Everything Else
  • Amazon Web Services (AWS) Service Integrations
  • Instance Types for Big Data  
  • Amazon Elastic Compute Cloud (Amazon EC Two) for Big Data
Lession 9: Preparing for the Exam
  • Exam Tips
  • State of Learning Checkpoint
  •  Exam Walkthrough and Signup
  • Save Fifty percent on your AWS Exam Cost
  • Get an Extra Thirty Minutes on your AWS Exam - Non - Native English Speakers Only
Lession 10: Appendix - Machine Learning Topics for the Amazon Web Services AWS Certified Big Data
  • Machine Learning Hundred and One
  • Classification Models
  • Amazon Machine Learning Service
  • Amazon SageMaker
  • Deep Learning Hundred and One
  • [Exercise] Amazon Machine Learning - Part One
  • [Exercise] Amazon Machine Learning - Part Two
Lession 11: Wrapping Up
  • Congratulations Now make sure you are ready

Session 2: Live Virtual Class Curriculum

Lession 1 : Course Introduction
  • Overview of Big Data on Certification Course
  • Overview of the Certification
  • Overview of the Course
Lession 2: AWS 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
Lession 3: 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
Lession 4: 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
Lession 5: Processing-1
  • 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
Lession 6: Processing-2
  • 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
Lession 7: 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
Lession 8: 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
Lession 9: Analysis with 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
Lession 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

Pratice Projects

Pratice Projects
  • Real-time Analytics on Streaming Data
  • Truegate S3 Replication Big Data Assignment

AWS Cloud Technical Essentials

Lesson 1: Introduction to AWS Cloud Practitioner Course
  • AWS CP Introduction
  • Introduction to AWS Cloud Practitioner Course
  • Domain Introduction
  • AWS Certification Path
  • Exam Details
Lesson 2: Core Concept of Cloud Computing
  • Learning Objectives
  • Networking Terminologies Part 
  • Networking Terminologies Part 
  • Client Server Architecture
  • Classic Data Centres
  • Virtualization
  • Basics of Cloud Computing
  • Cloud Computing Deployment Models
  • Public Cloud
  • Private Cloud
  • Hybrid Cloud
  • Community Cloud
  • Comparison of Deployment Models
  • Cloud Computing Service Models Part 
  • Cloud Computing Service Models Part
  • Pizza Analogy02:22
  • Cloud Service Providers
  • Summary
Lesson 3: Introduction to AWS
  • Learning Objective
  • AWS Overview
  • Demo Setting Up AWS Account
  • Gartner Research
  • Cloud Architecture Design Principles
  • Well Architected Framework
  • Operational Excellence
  • Security
  • Reliability
  • Performance Efficiency
  • Cost Management
  • AZ and Regions
  • CloudFront Infrastructure
  • Edge Locations
  • Networking and Content Delivery Services
  • Virtual Private Cloud(VPC)
  •  VPC Peering
  • VPC End Points
  • Domain Name System(DNS)
  • CDN0
  • CloudFront Infrastructure
  • Elastic Load Balancer
  • ELB Types
  • Compute Services
  • What is EC
  • EC2 Benefits and Features
  •  EC2 Creation Steps
  • Amazon Machine Image(AMI)
  •  EC2 Instance Types
  • EC2 Creation Steps(Continue)
  • Demo Launching EC2 Instance using AWS Console
  • AWS CLI
  •  Demo Launch an EC2 Instance using AWS Command Line Interface
  • EC2 Auto Scaling
  •  Elastic Beanstalk
  • AWS Storage Services
  •  Amazon S3(Simple Storage Service)
  • S3 Policies
  • Demo Create S3 Bucket and Bucket Policies
  •  Database Services
  • AWS Databases
  • Database Types
  • Relational Database Service(RDS)
  • Database Connection
  • Demo RDS Usage
  • Introduction to DynamoDB
  • Demo Managing AWS DynamoDB
  • Resource Groups and Tagging
  • Case Study
  • Demo Use of VPC and Subnet
  • Summary
Lesson 4: AWS Security and Compliance
  • Learning Objective
  • Security Aspects
  • Security and Compliance Principles
  •  AWS Access Control and IAM
  • IAM Working
  • Security BestPractices Part 1
  • Security Best Practices Part 2
  • Web Application Firewall
  • AWS Shield
  • Firewall Manager
  •  AWS CloudTrail
  • AWS CloudWatch
  • AWS Config Service
  • CloudWatch vs CloudTrail
  • AWS Config vs CloudTrail
  • AWS Inspector
  • AWS Trusted Advisor
  • Demo Managing IAM Service
  • Summary
Lesson 5: AWS Costing and Support Service
  • Learning Objective
  • Understand AWS Pricing
  • AWS Pricing Models
  • Cost Calculator
  • Support Plans
  • Marketplace
  • Demo Setup Billing Budget and Check Invoice
  • Summary

Admission details

AWS Big Data Certification Training Certification Course admission process has been mentioned below:

Step 1 - Visit the official website of www.simplilearn.com portal

Step 2 -Click on Enroll now button 

Step 3 - You will be redirected to a new page

Step 4 - Apply coupon if you have one or else click on the Proceed button. 

Step 5 -  Fill the essential details such as name, contact number and email 

Step 6 -Pay the fee and save the receipt of the transaction for future reference. 

FAQs

How to become an AWS Data engineer?

AWS Certified Data Analytics – Specialty Certification is a prerequisite for the candidates to become an AWS Data engineer. The AWS Big Data Certification Training course is designed specifically to prepare students for the certification exam.

Can the training course material help in preparing for the AWS Data Analytics-Specialty certification exam?

Yes. The study material offered by the AWS Big Data certification course is developed to help candidates prepare for the DAS-C01 exam.

What all is included in the AWS Big Data certification course?

Upon successful enrolment in the AWS Big Data certification training course, candidates will have access to high-quality eLearning content, simulation exam papers, and a handbook specially created for online participants for cross-reference to the eLearning content. 

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