- Big Data on AWS Certification Course Overview
- Overview of Big Data on AWS Certification Course
- Course Introduction
- Big Data on AWS Introduction
- Learning Objective
- Cloud computing and it's advantages
- Cloud Computing Models
- Cloud Service Categories
- AWS Cloud Platform
- Design Principles - Part One
- Design Principles - Part Two
- Why AWS for Big Data - Reasons and Challenges
- Databases in AWS
- Data Warehousing in AWS
- Redshift, Kinesis and EMR
- DynamoDB, Machine Learning and Lambda
- Elastic Search Services and EC
- Key Takeaways
- AWS Big Data Collection Services
- Learning Objective
- Amazon Kinesis and Kinesis Stream
- Kinesis Data Stream Architecture and Core Components
- Data Producer
- Data Consumer
- Kinesis Stream Emitting Data to AWS Services and Kinesis Connector Library
- Kinesis Firehose
- Transferring Data Using Lambda
- Amazon SQS, Lifecycle and Architecture
- IoT and Big Data
- IoT Framework
- AWS Data Pipelines and Data Nodes
- Activity, Pre-condition and Schedule
- 14Key Takeaways
- AWS Big Data Storage Services
- Learning Objective
- Amazon Glacier and Big Data
- DynamoDB Introduction
- DynamoDB and EMR
- DynamoDB Partitions and Distributions
- DynamoDB GSI LSI
- DynamoDB Stream and Cross Region Replication
- DynamoDB Performance and Partition Key Selection
- Snowball and AWS Big Data
- AWS DMS
- AWS Aurora in Big Data
- Demo - Amazon Athena Interactive SQL Queries for Data in Amazon S3 – Part 2
- Key Takeaways
- AWS Big Data Processing Services
- Learning Objective
- Amazon EMR0
- Apache Hadoop
- EMR Architecture
- EMR Releases and Cluster
- Choosing Instance and Monitoring
- Demo - Advance EMR Setting Options
- Hive on EMR
- HBase with EMR
- Presto with EMR
- Spark with EMR
- EMR File Storage
- AWS Lambda
- Key Takeaways
- Analysis
- Learning Objective
- Redshift Intro and Use cases
- Redshift Architecture
- MPP and Redshift in AWS Eco-System
- Columnar Databases
- Redshift Table Design - Part 2
- Demo - Redshift Maintenance and Operations
- Machine Learning Introduction
- Machine Learning Algorithm
- Amazon SageMaker
- Amazon Elasticsearch
- Amazon Elasticsearch Services
- Demo - Loading Dataset into Elasticsearch
- Logstash and R Studio
- Demo - Fetching the File and Analyzing it using RStudio
- Athena
- Demo - Running Query on S3 using the Serverless Athena
- Key Takeaways
- Visualization
- Learning Objective
- Introduction to Amazon QuickSight
- Visual Types
- Story
- Big Data Visualization
- Key Takeaways
- Security
- Learning Objective
- EMR Security and Security Group
- Roles and Private Subnet
- Encryption at Rest and In-transit
- Redshift Security
- Encryption at Rest using HSM
- Cloud HSM vs AWS KMS
- Limit Data Access
- Key Takeaways
- Home
- Simplilearn
- Courses
- AWS Data Analytics Certification Training
AWS Data Analytics Certification Training Course
Join AWS Big Data Certification training course by Simplilearrn to understand aspects of big data hosting and performing distributed processing on AWS platform.
Online
₹ 23,625
Quick facts
particular | details | ||
---|---|---|---|
Medium of instructions
English
|
Mode of learning
Self study, Virtual Classroom
|
Mode of Delivery
Video and Text Based
|
Frequency of Classes
Weekends
|
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
Fees information
To apply for the AWS Data Analytics Certification Training Course, students need to pay the requisite fee. AWS Big Data Certification Training Course fee details have been mentioned below:
Fee Structure
Training Options | Fee |
Blended Learning | Rs. 23,625 + Rs. 4,252.50 (CGST + SGST) = Rs. 27,877.50 |
Corporate Training | Not available |
certificate availability
certificate providing authority
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
- 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.
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
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.
The syllabus
Self-paced Curriculum
Live Virtual Class Curriculum
- Course overview of AWS Certified Data Analytics - Speciality Course
- Overview of the Certification
- Overview of the Course
- Project highlights
- Course Completion Criteria
- AWS in Big Data Introduction
- Introduction to Cloud Computing
- Cloud Computing Deployments Models
- Types of Cloud Computing Services
- AWS Fundamentals
- AWS Cloud Economics
- AWS Virtuous Cycle
- AWS Cloud Architecture Design Principles
- Why AWS for Big Data - Challenges
- Databases in AWS
- Relational vs Non-Relational Databases
- Data Warehousing in AWS
- AWS Services for collecting, processing, storing, and analyzing big data
- Key Takeaways
- Deploy a Data Warehouse Using Amazon Redshift
- Collection
- AWS Big Data Collection Services
- Fundamentals of Amazon Kinesis
- Loading Data into Kinesis Stream
- Assisted Practice: Loading Data into Amazon Storage
- Kinesis Data Stream High-Level Architecture
- Kinesis Stream Core Concepts
- AWS Services and Amazon Kinesis Data Stream
- How to Put Data into Kinesis Stream?
- Kinesis Connector Library
- Amazon Kinesis Data Firehose
- Assisted Practice: Transfer Data into Delivery Stream using Firehose
- Assisted Practice: Transfer VPC Flow log to Splunk using Firehose
- Data Transfer using AWS Lambda
- Assisted Practice: Backing up data in Amazon S3 using AWS Lambda
- Amazon SQS
- IoT and Big Data
- Amazon IoT Greengrass
- AWS Data Pipeline
- Components of Data Pipeline
- Assisted Practice: Export MySQL Data to Amazon S3 Using AWS Data Pipeline
- Key Takeaways
- Streaming Data with Kinesis Data Analytics
- Storage
- AWS Bigdata Storage services
- Data lakes and Analytics
- Data Management
- Data Life Cycle
- Fundamentals of Amazon Glacier
- Glacier and Big Data
- 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
- Use cases: Capturing Table Activity with DynamoDB Streams
- Cross-Region Replication
- Assisted Practice: Create a Global Table using DynamoDB
- DynamoDB Performance: Deep Dive
- Partition Key Selection
- Snowball & AWS BigData
- Assisted Practice: Data Migration using AWS Snowball
- AWS DMS
- AWS Aurora in BigData
- Assisted Practice: Create and Modify Aurora DB Cluster
- Storing and Retrieving the Data from DynamoDB
- 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
- Setup Hue for LDAP
- Assisted Practice: Configure HUE for LDAP Users
- Hive on EMR
- Assisted Practice: Set Up a Hive Table to Run Hive Commands
- Key Takeaways
- 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
- 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
- Redshift Data types
- RedShift Data Loading
- COPY Command for Data Loading
- RedShift Loading Data
- Key Takeaways
- ETL with Redshift
- Fundamentals of Machine Learning
- The 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
- Key Takeaways
- Fraud Detection Using Classification Algorithms on AWS Sagema
- Analysis with Machine Learning
- 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
- Analysis and Visualization
- 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
- STS and Cross Account Access
- Cloud Trail
- Key Takeaways
Project 1 - Real Time Analytics on Streaming Data with Amazon Kinesis and Amazon Elasticsearch Service
In this project, students will assist Facebook to monitor the system and detect any sentiment change in a social media feed. Also, help react to the sentiment change in real-time.
Project 2 - Real-Time Analytics on Streaming Data
Analyse a stream of data obtained from an IoT temperature sensor device in real-time via a big data stack for data engineering.
Project 3 - Transactional Data Analysis
This project involves the use of big stack data for data engineering to analyse transactions, convey scalable insights, and share patterns.
Evaluation process
The exam fee for the course is USD 300 and the exam duration is 170 minutes.
FAQs
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.
The fee for the AWS Big Data Certification Training Certification Course certification exam is 300 USD.
A total of 170 minutes is allotted to the candidates to complete the DAS-C01 exam.
It will take approximately 40-45 hours to complete the AWS Big Data certification course by Simplilearn.
Yes. The study material offered by the AWS Big Data certification course is developed to help candidates prepare for the DAS-C01 exam.
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.