Big Data Online Live Class by Experts
Our Training/Internship Process
Big Data - Syllabus, Fees & Duration
MODULE 1: Introduction to Big Data and Hadoop
- Types of Digital Data
- Introduction to Big Data
- Big Data Analytics
- History of Hadoop
- Apache Hadoop
- Analysing Data with Unix tools
- Analysing Data with Hadoop
- Hadoop Streaming
- Hadoop Echo System
- IBM Big Data Strategy
- Introduction to Infosphere BigInsights
- Big Sheets
MODULE 2: HDFS (Hadoop Distributed File System)
- The Design of HDFS
- HDFS Concepts
- Command Line Interface
- Hadoop file system interfaces
- Data flow
- Data Ingest with Flume and Scoop and Hadoop archives
- Hadoop I/O: Compression
- Serialization
- Avro and File-Based Data structures
MODULE 3: Map Reduce
- Anatomy of a Map Reduce Job Run
- Failures, Job Scheduling
- Shuffle and Sort
- Task Execution
- Map Reduce Types and Formats
- Map Reduce Features
MODULE 4: Hadoop Eco System
- Pig : Introduction to PIG
- Execution Modes of Pig
- Comparison of Pig with Databases
- Grunt, Pig Latin
- User Defined Functions
- Data Processing operators
- Hive : Hive Shell
- Hive Services
- Hive Metastore
- Comparison with Traditional Databases
- HiveQL
- Tables
- Querying Data and User Defined Functions
- Hbase: HBasics
- Concepts
- Clients
- Hbase Versus RDBMS
- Big SQL: Introduction
MODULE 5: Data Analytics with R
- Machine Learning: Introduction
- Supervised Learning
- Unsupervised Learning
- Collaborative Filtering
- Big Data Analytics with BigR.
This syllabus is not final and can be customized as per needs/updates
- Since 2001, Making IT Experts by Experts
- Duration: 30 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsHybrid.com
- Training/Internship Certificate
- Atlanta
- Austin
- Baltimore
- Boston
- Charleston
- Charlotte
- Chicago
- Colorado Springs
- Columbus
- Dallas
- Denver
- Detroit
- Fort Worth
- Fresno
- Honolulu
- Houston
- Indianpolis
- Jacksonville
- Kansas City
- Las Vegas
- Los Angeles
- Lousville
- Memphis
- Miami
- Milwaukee
- Minneapolis
- Nashville
- New Orleans
- New York
- Oklahoma City
- Omaha
- Philadelphia
- Phoenix
- Portland
- Raleigh
- Sacramento
- San Antonio
- San Diego
- San Francisco
- San Jose
- Seattle
- Tampa
- Tucson
- Tulsa
- Virginia Beach
- Washington
- Wichita
Course Highlights
Our Locations
Real-life As an illustration of the event, execution, and deployment of an enormous range of new big-data solutions, Big Data applications and workflows in many fields are provided as use cases. NESTSOFT Big Data Training is designed to turn you become a certified Big Data specialist by providing you with extensive hands-on experience. Experienced industry specialists with more than ten years of experience cover in-depth knowledge of Big Data and Ecosystem technologies. Our skilled instructors may train you during the web training. When it comes to seeking for the best jobs, having the Big Data certification can put you in a different group. Big data analytics enables businesses to integrate their data and use it to identify new opportunities.
Big data refers to methods for analysing, methodically extracting information from, or generally dealing with data collections that are too large or complicated for typical data-processing application software to handle. The big data course in location is designed to prepare students for a future as Big Data Engineers in the industry. The NESTSOFT Big Data course covers a wide range of topics in big data, including data generation, storage, management, and transfer, as well as analytics, with a focus on cutting-edge technologies, tools, architectures, and systems that make up big-data computing solutions in high-performance networks. Students who complete NESTSOFT's massive data course will be able to: Identify Big Data and its Business Implications, List the components of Hadoop and Hadoop Eco-System, Access and Process Data on Distributed File Systems, Manage Job Execution in Hadoop Environment, Develop Big Data Solutions using Hadoop Eco System, Analyze Infosphere Big Insights Big Data Recommendations, and Apply Machine Learning Techniques in R. 
