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Big Data & AWS

Big Data, AWS and Hadoop

Gain access to the potential of Big Data through our all-encompassing training program on Big Data, AWS, and Hadoop. This course is carefully crafted to provide you with the necessary expertise and resources to thrive in the dynamic realm of data analysis. Delve into an immersive educational journey where you will perfect the techniques of handling, manipulating, and interpreting large data sets utilizing the cutting-edge services offered by AWS.

Participants in this course will gain practical experience using essential technologies such as Amazon S3, EMR, Redshift, Athena, Glue, Lambda, SQS, QuickSight, SageMaker, CloudTrail, and other tools, applied within realistic scenarios.

Big Data, AWS and Hadoop Course Overview

  • Immersive Classroom Experience
  • Immersive Plus Online Blended Learning
  • Hands-on Training By Industry Experts
  • Practical Hands-on Capstone Projects
  • 200+ Hours of Learning & Practicals
  • 15+ Programming Tools & Technologies
  • Globally Recognized Dual Certification
  • Real World Projects and Case Studies
  • Big Data Hadoop with AWS
  • Machine Learning for Big Data
  • Live RIA® DoubtBuster Sessions
  • No Cost EMI Options Available
  • 360 Degree Career Support
  • In-person Career Mentorship (1:1)
  • In-person Job Interview Preparation (1:1)
  • Exclusive Job Opportunities Portal
  • Access to Top MNC Companies
  • RIA® Alumni Status

Syllabus for Big Data, AWS and Hadoop Course

Immerse yourself in a comprehensive learning experience featuring more than 200 hours of engaging content and hands-on activities in our specially created course on Big Data, AWS, and Hadoop. The curriculum has been carefully structured to offer current insights and practical exposure to the most recent AWS advancements and Big Data applications. Crafted by top professionals in the field, this course delivers a state-of-the-art educational journey, empowering you with the expertise required to excel in managing, processing, and analyzing data on a worldwide level.

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Topics That Will Keep You Engaged and Curious

Delve into the ever-changing realm of Big Data by gaining practical knowledge in advanced AWS tools and Hadoop systems. Discover and work with a variety of technologies such as Amazon S3, EMR, Redshift, Athena, Glue, Lambda, SQS, QuickSight, SageMaker, CloudTrail, and others, all connected to real-life scenarios. Keep up with the latest in Big Data through interactive lessons and hands-on exercises that provide an enjoyable and fruitful learning experience.

Your Roadmap to Learning

Start with the basics and then move on to more complex subjects slowly. This method helps avoid feeling overwhelmed, which in turn aids in retaining and comprehending new ideas. Every topic is interconnected, forming a strong base for a more thorough comprehension.

Ideal Candidates for Big Data, AWS and Hadoop Course

This course on Big Data, AWS and Hadoop is available to students from various backgrounds such as Commerce, Arts, Banking, Engineering, and Science. It is designed for professionals looking to transition or enhance their skills in this advanced industry. Valuable knowledge and perspectives are ready to be gained through this educational journey.

Minimum Eligibility for Big Data, AWS and Hadoop Course

In the current job market driven by skills, a passion for learning outweighs degrees. A high school diploma is ample to launch this journey. Your passion for big data and eagerness to harness new-age technology will drive your career. Acquire skills that not only unlock doors but also forge new professional horizons.

Job Opportunities After Big Data, AWS and Hadoop Course

Roles in the field of data include Big Data Engineer, Data Analyst, Data Scientist, Data Engineer, Cloud Data Architect, Business Intelligence Developer, Hadoop Developer, Machine Learning Engineer, AWS Solutions Architect, and Data Operations

Industries That Are Hiring Big Data, AWS and Hadoop Specialists

The demand for Big Data and Hadoop specialists spans across diverse sectors, including Technology, Finance, Healthcare, Retail, Telecommunications, Manufacturing, Energy, Transportation and Logistics, Government, Marketing and Advertising, Insurance, Education, Media and Entertainment, Agriculture, Pharmaceuticals, Hospitality, Human Resources, Real Estate, E-commerce and Environmental Monitoring

Globally Accredited Big Data, AWS and Hadoop Course in India

Explore the realm of Big Data, AWS, and Hadoop through the leading course offered by the RASA Institute of Analytics in India. Known for its thorough training, this program covers the complete lifecycle of Big Data, AWS, and Hadoop, including areas like Data Collection, Storage, Ingestion, Processing, Advanced Analysis Techniques, Governance, Compliance, and NLP for Big Data. Dive into various skills and tools like Hadoop & Spark meticulously detailed in the course curriculum.

At RASA Institute of Analytics, we provide more than just training – we present a route to achieving success. Enroll in our Big Data, AWS, and Hadoop Course in India to start on the path to becoming a highly sought-after Big Data Analyst in the country.

Why Should You Choose RASA Institute of Analytics for Big Data, AWS and Hadoop Course in India?

Begin your path to a successful career in Big Data, AWS, and Hadoop at the esteemed RASA Institute of Analytics, a top training center for these fields in India. With a strong history of guiding aspiring Big Data Analysts to success both locally and internationally, we are recognized for our excellence in the industry. Learn from our experienced trainers, each with extensive background in Big Data, AWS, and Hadoop. Our detailed course content is designed to prepare you with the necessary expertise to thrive in the competitive world of Big Data, AWS, and Hadoop in India.

Explore our AI Powered Centralized Learning Hub

Our advanced Learning Management System harnesses artificial intelligence to create a central platform aimed at improving your educational journey. It grants you convenient entry to learning resources, class recordings, individualized progress monitoring, submission of assignments, and automated assessment. Furthermore, it includes the RIA® DoubtBuster feature to assist in resolving any uncertainties you might encounter.

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Course Sylabus

  • Big Data, AWS and Hadoop Course: Orientation

    Quickly grasp the course material and important ideas, all while setting up necessary software. This initial session sets a solid foundation for your future progress, reducing barriers in your learning process.

    Course Expectations and Structure
    • Overview of the Big Data, AWS and Hadoop Course Modules
    • Brief on Assignments and Assessments
    Introduction to the Learning Environment
    • Digital Platforms and Resources
    • Communication Channels
  • Introduction to AWS and Big Data Analytics
    Overview of AWS and Big Data
    • Introduction to Amazon Web Services (AWS)
    • Overview of Big Data Concepts
    • Use Cases and Benefits of Big Data Analytics
    • Key AWS Big Data Services: S3, EMR, Redshift, Athena, Glue, QuickSight
    Setting Up AWS Environment
    • Creating an AWS Account
    • Navigating the AWS Management Console
    • Understanding AWS Free Tier: Limits and Quotas
    • AWS Billing and Cost Management Basics
    Introduction to Amazon S3
    • Overview of Amazon S3
    • Creating and Managing S3 Buckets
    • Uploading and Organizing Data
    • Data Security: Bucket Policies, IAM Policies, and Encryption
  • Data Processing with Amazon EMR
    Introduction to Amazon EMR
    • Overview of Amazon EMR
    • EMR Architecture and Components
    • Launching and Configuring an EMR Cluster
    • Understanding Cluster Node Types and Configuration
    Hadoop and HDFS on EMR
    • Basics of Hadoop Distributed File System (HDFS)
    • Data Storage and Management in HDFS
    • Running MapReduce Jobs on EMR
    • Managing HDFS Data: Storage and Retrieval
    Apache Spark on EMR
    • Introduction to Apache Spark
    • Spark Architecture: Driver, Executors, and Cluster Manager
    • Running Spark Jobs on EMR
    • Basic Spark Operations: RDDs and DataFrames
    Advanced Spark Techniques
    • Using Spark SQL for Querying Data
    • Working with Spark Streaming for Real-Time Data Processing
    • Optimizing Spark Jobs: Performance Tuning and Caching
    Data Processing with Apache Hive
    • Introduction to Apache Hive
    • Creating and Managing Hive Tables
    • Writing and Executing HiveQL Queries
    • Integrating Hive with Hadoop and Spark
  • Data Warehousing and Analytics
    Introduction to Amazon Redshift
    • Overview of Amazon Redshift Data Warehouse
    • Setting Up and Configuring a Redshift Cluster
    • Loading Data into Redshift: COPY Command and Data Formats
    • Managing Redshift Clusters: Scaling and Performance
    Redshift Data Warehousing Concepts
    • Designing Redshift Schema: Distribution Keys and Sort Keys
    • Query Optimization: Analyzing Query Plans and Execution
    • Using Redshift Spectrum to Query S3 Data
    • Managing Workloads: Concurrency Scaling and Workload Management (WLM)
    Data Analytics with Amazon Athena
    • Introduction to Amazon Athena
    • Running SQL Queries on Data in S3
    • Using Athena for Ad-Hoc Analysis
    • Performance Tips: Partitioning and Optimization
    Building Data Lakes with AWS Lake Formation
    • Overview of AWS Lake Formation
    • Setting Up a Secure Data Lake
    • Data Cataloging and Metadata Management
    • Data Governance: Access Control and Security
  • Data Ingestion and Integration
    Data Ingestion with AWS Glue
    • Introduction to AWS Glue
    • Creating and Managing Glue Crawlers
    • Building ETL Pipelines with Glue Jobs
    • Data Transformation and Cleaning Using Glue
    Data Migration with AWS Database Migration Service (DMS)
    • Overview of AWS DMS
    • Setting Up and Configuring Data Migration Tasks
    • Migrating Data from Various Sources to AWS
    • Monitoring and Managing Migration Tasks
    Data Processing with AWS Lambda and Amazon SQS
    • Introduction to AWS Lambda
    • Setting Up Lambda Functions for Data Processing
    • Using Amazon SQS for Message Queuing
    • Real-Time Data Processing with Lambda and SQS
  • Data Visualization and Business Intelligence
    Introduction to Amazon QuickSight
    • Overview of Amazon QuickSight
    • Connecting Data Sources to QuickSight
    • Creating Basic Dashboards and Visualizations
    • Sharing and Publishing Dashboards
    Advanced QuickSight Techniques
    • Creating Custom Visualizations
    • Using Calculated Fields and Advanced Analytics
    • Sharing and Collaborating on Dashboards
    • Embedding QuickSight Visualizations in Applications
    Business Intelligence Strategies
    • Best Practices in Business Intelligence (BI)
    • Implementing Data-Driven Decision Making
    • Case Studies and Real-World Applications of BI
  • Machine Learning and AI in Big Data
    Introduction to AWS Machine Learning Services
      • Overview of AWS Machine Learning Services
      • Using Amazon SageMaker for Building ML Models
      • Training and Deploying Machine Learning Models on SageMaker
      • Basic ML Algorithms and Use Cases
    Big Data and AI Integration
      • Integrating Big Data with AI for Enhanced Insights
      • Practical Use Cases and Applications
      • Ethical Considerations and Best Practices in AI
  • Security and Compliance in Big Data
    Data Security Fundamentals
      • AWS Security Best Practices
      • Data Encryption Techniques: At-Rest and In-Transit
      • Implementing Access Controls and Security Policies
    Managing Permissions and Auditing
      • AWS Identity and Access Management (IAM) Basics
      • Monitoring and Logging with AWS CloudTrail
      • Conducting Security Audits and Compliance Checks
  • Capstone Project

    Demonstrate your abilities by putting them into practice through a practical project that reflects your understanding of the course material.

    Capstone Project Allocation, Mentorship and Presentation
    • Project and Dataset Assignment by Capstone Mentor
    • Orientation Session by Capstone Mentor – Project Expectations
    • Mentorship Session by Capstone Mentor – Doubt Resolutions
    • Project Presentation
  • Career Enhancement

    Enhance your professional path by acquiring abilities, knowledge, and tactics to progress in the ever-evolving areas of Data Science and Artificial Intelligence.

    Soft Skills Training
    • Presentation Skills
    • Email Etiquettes
    • LinkedIn Profile Building
    • Personality Development and Grooming
    Interview Preparation
    • Interview Do’s and Don’ts
    • Mock Interviews
    • HR And Technical Interview Prep
    • One-On-One Feedback

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