Learn BIG DATA Complete Guide (OFFLNE)

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The volume of data that one has to deal has exploded to unimaginable levels in the past decade, and at the same time, the price of data storage has systematically reduced. Private companies and research institutions capture terabytes of data about their users’ interactions, business, social media, and also sensors from devices such as mobile phones and automobiles. The challenge of this era is to make sense of this sea of data.

This is where big data analytics comes into picture. Big Data Analytics largely involves collecting data from different sources, munge it in a way that it becomes available to be consumed by analysts and finally deliver data products useful to the organization business. The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics. In this tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics.

We Cover Topics Like

• Data Life Cycle

• Methodology

• Core Deliverables

• Key Stakeholders

• Data Analyst

• Data Scientist

Big Data Analytics Project

• Problem Definition

• Data Collection

• Cleansing data

• Data Visualization

• Data Exploration

• Summarizing

Big Data Analytics Methods

• Introduction to R

• Charts & Graphs

• Data Tools

• Statistical Methods

Advanced Methods

• Machine Learning for Data Analysis

• Naive Bayes Classifier

• K-Means Clustering

• Association Rules

• Decision Trees

• Logistic Regression

• Time Series

• Text Analytics

• Online Learning