Data Science and Big Data Analytics is about harnessing the power of data for new insights.

The App covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software.

Big Data Analytics course will inspire you to explore opportunities in the world of big data analytics. This app will take you from the basics of big data analytics to the advance analytical tools, methods and technology, which could be used for the big data analytics projects. This is a must basic course for those who wants to make a career in data science.

We are living in the dawn of what has been termed as the "Fourth Industrial Revolution", which is marked through the emergence of "cyber-physical systems" where software interfaces seamlessly over networks with physical systems, such as sensors, smartphones, vehicles, power grids or buildings, to create a new world of Internet of Things (IoT). Data and information are fuel of this new age where powerful analytics algorithms burn this fuel to generate decisions that are expected to create a smarter and more efficient world for all of us to live in. This new area of technology has been defined as Big Data Science and Analytics, and the industrial and academic communities are realizing this as a competitive technology that can generate significant new wealth and opportunity. Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. Big data science and analytics deals with collection, storage, processing and analysis of massive-scale data. Industry surveys, by Gartner and e-Skills, for instance, predict that there will be over 2 million job openings for engineers and scientists trained in the area of data science and analytics alone, and that the job market is in this area is growing at a 150 percent year-over-year growth rate. Also for big data service providers who may be interested in offering a broader perspective of this emerging field to accompany their customer and developer training programs. The typical reader is expected to have completed a couple of courses in programming using traditional high-level languages at the college-level, and is either a senior or a beginning graduate student in one of the science, technology, engineering or mathematics (STEM) fields.

This course covers following contents in depth

Tools for Big Data Analysis and Deep Learning

Python Introduction Why Python is popular?

Python Libraries for handling Big Data Exploration and Visualization

Introduction to Databases, Apache Hadoop, Apache Spark, IoT

Relational Databases

NoSQL, NewSQL Databases

MongoDB JSON Document Database

Microsoft Azure HD Insight

Tweeter API

Apache Hadoop, HDFS, MapReduce, YARN

IoT, IoT Issues, Publish and Subscribe Model

This App will help you:

Become a contributor on a data science team
Deploy a structured lifecycle approach to data analytics problems
Apply appropriate analytic techniques and tools to analyzing big data
Learn how to tell a compelling story with data to drive business action
Prepare for EMC Proven Professional Data Science Certification

Who this course is for:
Beneficial to recent graduates looking to get a foothold in the IT Industry.
IT managers looking to better manage data analysis.
Businesses looking to organize and analyze large amounts of vital data in order to improve business insights.
Managers wanting to reach business goals and improve agility.
IT professionals looking to implement new data analysis tools.