Big Data Training by Experts
Our Training 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 jobsNEAR.in
- Training/Internship Certificate
- Web Development Courses in Calgary
- Mobile App Develpment Courses in Calgary
- Website Design Courses in Calgary
- Networking and Security Courses in Calgary
- Digital Marketing (SEO) Courses in Calgary
- Graphics Training Courses in Calgary
- Cloud Computing Courses in Calgary
- Mean Stack Development Courses in Calgary
- Python Full Packages Courses in Calgary
- Animation & Video Editing Courses in Calgary
- Mern Stack Development Courses in Calgary
Course Highlights
Featured Courses
Python, JavaScript, and Java are among the languages utilised.
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. 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. You can land your dream positions like Data Engineer, Big Data Lead, Technical Program Manager, Big Data Developer, and Product Engineer by completing a Big Data certification course from location.
Our Big Data certification will assist you in seizing this opportunity in your career. This on-site Big Data training will get you up and running in the most difficult professional abilities.
Big Data is the newest and most promising technology for processing large amounts of data and performing data analytics. As a result, smarter professional decisions are made, operations are well-organized, profits are higher, and clients are happier. When evaluating all of the tools accessible in information technology today, Big Data is one of the most promising disciplines. 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.
