Big Data Analytics Training Using R and Hadoop

Big Data Analytics Training Using R and Hadoop

 

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About The Event


Instructors
Sandeep Karanth
Founder, Scibler

Sandeep Karanth, founder of Scibler, a search technology firm has a career spanning 10+ years working in services and product companies. After his Master's, he started his stint at Microsoft in the Windows team in Redmond working on Internet Sharing and Contact Sync for Windows XP SP2 and Vista. When an opportunity arose to be part of a v1 product, he moved to the Office Live team building hosted IT services for SMEs. At Office Live, he was part of the backend team building user profile and offer management services and dealing with service integration, partner on boarding and zero-downtime data migration. In 2008, he returned to India to join Microsoft Research at Bangalore and has worked on a bunch of early stage development projects in security, green computing and Big Data analytics. His role here ranges from architecting & building necessary infrastructure, leading projects from ideation to deployment and transferring relevant research into Microsoft products. Click here to see more information.

 

About The Big Data Analytics Course


This course provides a blend of theoretical and practical training, which will enable the students to participate in big data and analytics projects. It covers a wide range of topics from basics to becoming an independent analyst. We will be using the R as a statistical tool and Hadoop to handle some of the publicly available Big Data to deliver on insights with the dual objective to impart best practices and equipping the analysts with necessary toolkit.
Big Data Analytics Course Objective

Upon successful completion of this course, participants should be able to:

Immediately participate and contribute as a Data Science Team Member on big data and other analytics projects by:

  1. Deploying the Data Analytics Lifecycle to address big data analytics projects
  2. Reframing a business challenge as an analytics challenge
  3. Applying appropriate analytic techniques and tools to analyze big data, create statistical models, and identify insights that can lead to actionable results
  4. Selecting appropriate data visualizations to clearly communicate analytic insights to business sponsors and analytic audiences
  5. Using tools such as: R, Map Reduce/Hadoop, in-database analytics

 

 

Who should learn Big Data Analytics?

This course is intended for individuals seeking to develop an understanding of Data Science from the perspective of a practicing Data Scientist, including:

  1. Managers of teams of business intelligence, analytics, and big data professionals
  2. Current Business and Data Analysts looking to add big data analytics to their skills.
  3. Data and database professionals looking to exploit their analytic skills in a big data environment.
  4. Recent college graduates and graduate students with academic experience in a related discipline looking to move into the world of Data Science and big data.

  

Pre-requisites


To complete this course successfully and gain the maximum benefits from it, a student should have the following knowledge and skill sets:

  1. Familiarity with basic statistics, good command over a scripting language and beginner level knowledge in SQL.



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