Everyday huge amount of data is created. This data comes from everywhere : sensors used to gather climate information, post to social media sites, digital pictures and videos, purchase transaction records and Cell phone GPS signals to name a few. This data is Big Data.
Big data is a blanket term for any collection of data set so large and complex that it becomes difficult to process using on hand data management tools or traditional data processing applications. The challenges include capture, storage, search, sharing, transfer, analysis and visualization. Anyone who has knowledge on Java, basic UNIX and basic SQL can opt for Big Data training course.
What is a Virtual Class?
A Virtual Class is an online class that allows participants to communicate, view presentations and interact with trainers. Participants attend virtual class by connecting to the Internet rather than traveling to a physical classroom. Virtual class provides the benefit of flexibility and allows participants to attend classes that may not be offered in smaller cities. It is also beneficial for professionals who are extremely busy and cannot take out times to attend classes.
Virtual classes with International Academy
The Virtual Classes will be conducted over the weekends. The virtual class is right in your comfort zone, you can attend this classes from your home or office. This will also provide you an opportunity to interact with the trainers and get your queries solved. Each virtual class will be recorded, in case you have missed any class, you can request for the virtual class link over the mail.
Note: To attend the Virtual Classrooms, you need to have computer & internet connection with the minimum speed of 1 Mbps.
Suggested Duration: 3 months
Mode of Learning:
Learning (Self Paced)
Learning (Trainer Led Training)
Windows 7 OS
Min 8 GB RAM
Quad core processor
Further Learning Roadmap:
To learnanalytics further and orient your career in that direction, following are the recommended study areas –
Business Analytics, Business Intelligence
Big Data Programming
Predictive Analytics and Data Modelling
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Copyright International Business Machines Corporation 2015. This document may not be reproduced in whole or in part without the prior written permissionof IBM
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