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  1. About the Course
  2. Intended Audience
  3. Syllabus

COURSE OVERVIEW

The Data Science and Big Data Analytics course gives down to earth establishment level preparing that empowers prompt and successful interest in Big Data and different Analytics ventures. It incorporates a prologue to Big Data and the Data Analytics lifecycle to address business challenges that influence Big Data. The course gives establishing in essential and progressed systematic techniques and a prologue to Big Data Analytics innovation and instruments. Lab sessions offer chances to see how these strategies and devices might be connected to true business challenges by a rehearsing Data Scientist. This course gives an industry accreditation to business investigators, information distribution center specialists or different experts with comparative foundations to help them change into the universe of Data Science and Big Data Analytics that has extraordinary difficulties and opportunities.

 

Course Outline

Introduction

  • Introduction to NoSQL Architecture with MongoDB
  • How does MongoDB compare to other NoSQL solutions and to traditional databases
  • MongoDB a gateway drug to NoSQL
  • Caveats and Problems that MongoDB is not good at solving
  • The sweet-spot for MongoDB
  • Installing and setting up MongoDB

Working with Database, Collections, Document, Fields

  • Using the console (with lab)
  • Introduction to MongoDB commands (with lab)
  • Creating a Database, Collection and Documents (with lab)
  • Simple Querying (with lab)
  • Understanding and working with indexes (with lab)

Architecture Deep Dive

  • Working with Replica Sets
  • What is the simplest setup to get started
  • Working with Journaling
  • Understanding data safety versus throughput tradeoffs
  • Autosharding: who should use it and tradeoffs
  • Massively scaling MongoDB
  • Know your application and don’t kill a flea with a sledge hammer

Using the MongoDB Aggregation Framework

Using Map Reduce with MongoDB

Java and MongoDB

  • Setting up MongoDB and Java
  • Setting up Eclipse to work with MongoDB
  • Working with Databases and Collections (with lab)
  • Creating documents (with lab)
  • Performing queries (with lab)
  • Working with aggregation API (with lab)
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