Big Data, AWS and Hadoop

Unlock the power of Big Data with our comprehensive Big Data, AWS and Hadoop course, designed to equip you with the essential skills and tools to excel in the rapidly evolving field of data analytics. Immerse in the learning experience where you will master the art of managing, processing, and analyzing vast amounts of data using AWS’s state-of-the-art services.

This course offers hands-on practice with key technologies like Amazon S3, EMR, Redshift, Athena, Glue, Lambda, SQS, QuickSight, SageMaker, CloudTrail and more, all integrated with real-world use cases.

Certification: Certified Big Data Practitioner & Data Analytics Professional

The Most In-Demand and Highly Paid Skills

Learning Paths

Certification (4 Months) | Diploma (6 Months)

1000+ Learners

Trained Students Across The Country

360° Career Support

Resume Building, Interview Prep, and Access to Partner Companies

Course Key Highlights

Immersive Hybrid Learning Experience (Classroom + Online)

Recognized Certification in Big Data & Cloud Technologies

100+ Hours of Hands-On Training with Real-Time Data Projects

Enterprise-Grade Big Data Capstone Projects

Mastery of Hadoop Ecosystem (HDFS, MapReduce, Hive, Pig, Spark)

Exclusive Access to Cloud & Big Data Job Roles

Advanced Data Architecture & Distributed Computing Concepts

Integration of AWS Services (EC2, S3, EMR, Lambda, Redshift)

End-to-End Data Pipeline Deployment & Automation

Live Projects with Real-Time Data Streaming & Processing

Efficient Data Storage & Management with NoSQL & Relational Databases

Cloud Infrastructure Setup & Monitoring with AWS Tools

Practical Training in Scalable Data Solutions

Live Debugging, Query Optimization & Troubleshooting Sessions

360° Career Support & Resume Building for Data Roles

1:1 Career Mentorship with Cloud & Data Experts

1:1 Job Interview Preparation for Big Data & AWS Roles

Direct Access to Hiring Networks of Top MNCs

Globally Accredited Big Data, AWS and Hadoop Course in India

Delve into the entire Big Data, AWS and Hadoop lifecycle, encompassing Data Collection, Data Storage, Data Ingestion and Processing, Advanced Data Analysis Techniques, Data Governance and Compliance, Natural Language Processing (NLP) for Big Data, and beyond. Explore a vast array of skills and tools, such as Hadoop & Spark, all meticulously covered in our Big Data, AWS and Hadoop course curriculum in India.

Why Should You Choose Big Data, AWS and Hadoop Course?

Embark on a transformative journey towards a rewarding career in Big Data, AWS and Hadoop. With a proven track record shaping the careers of many Big Data Analysts, both locally and internationally, we stand as a beacon of excellence in the Big Data, AWS and Hadoop field. Benefit from our expert trainers, each possessing years of professional experience in Big Data, AWS and Hadoop. Our comprehensive Big Data, AWS and Hadoop Course curriculum is tailored to equip you with the skills and knowledge needed to excel in the competitive landscape of Big Data, AWS and Hadoop in India.

Course Overview

This course provides a comprehensive understanding of Big Data concepts, focusing on the Hadoop ecosystem and its integration with Amazon Web Services (AWS). You'll learn to process, store, and analyze large datasets using industry-standard tools and cloud infrastructure.

Defining the 5 Vs: Volume, Velocity, Variety, Veracity, Value
Challenges and Opportunities in Big Data
Traditional Data Processing vs. Big Data Processing

Data Ingestion, Storage, Processing, and Analysis
Batch Processing vs. Stream Processing

Hadoop Architecture: HDFS, YARN, MapReduce
Core Components and Their Roles
Setting up a Single-Node Hadoop Cluster (Local)

HDFS Architecture: NameNode, DataNode
Replication, Fault Tolerance, and Data Locality
HDFS Commands and File Operations

YARN Architecture: ResourceManager, NodeManager, ApplicationMaster
Resource Scheduling and Job Execution

Understanding Map and Reduce Phases
Writing and Executing MapReduce Jobs (Java/Python)
Combiners, Partitioners, and Custom Writable Comparators

Hive Architecture and Metastore
Hive Query Language (HQL) for Data Analysis
Managed vs. External Tables, Partitions, and Buckets

Introduction to Pig Latin
Data Flow Operations and UDFs

HBase Architecture and Data Model
CRUD Operations in HBase
Integration with Hadoop

Importing Data from RDBMS to HDFS
Exporting Data from HDFS to RDBMS

Introduction to AWS Ecosystem
IAM (Identity and Access Management) for Security
VPC (Virtual Private Cloud) and Networking Basics

Amazon S3 (Simple Storage Service) for Data Lake
Amazon EBS (Elastic Block Store) and Instance Store

Amazon EC2 (Elastic Compute Cloud) for Cluster Hosting
AWS Lambda for Serverless Data Processing

Amazon EMR (Elastic MapReduce) for Managed Hadoop/Spark
Amazon Kinesis for Real-time Data Streaming
Amazon Redshift for Data Warehousing
AWS Glue for ETL and Data Catalog
Amazon Athena for Interactive Querying

Introduction to Spark Architecture (RDDs, DataFrames)
Spark SQL for Structured Data
Spark Streaming for Real-time Processing
Machine Learning with Spark MLlib

Apache Kafka for Distributed Messaging
Flume and Flink for Data Ingestion and Stream Processing

Data Lineage, Quality, and Metadata Management
Data Encryption and Access Control in Big Data

Requirements Gathering and Architecture Design
Choosing the Right Tools and Technologies

Setting up an EMR Cluster for Data Processing
Ingesting Data into S3 and Processing with Spark/Hive
Visualizing Results with BI Tools (e.g., Tableau, QuickSight)

Analyzing Large-scale Logs
Building Recommendation Systems
Fraud Detection with Big Data

Enrollment Process

Step 1

Application Submission

Prospective students complete and submit an online application form, providing essential profile details for enrolling in the Course / Training.

Step 2

Application Review and Discovery

After a thorough review of applications by the academics team, qualified candidates receive a call from our experienced counselor who guides them with the details of the Course / Training

Step 3

Enrollment Offer

Successful candidates receive an offer of admission, and upon acceptance, proceed to complete the enrollment process. This includes submitting necessary documents, paying fees, and attending an orientation session to kickstart their educational journey

Big Data, AWS and Hadoop