HSR Layout, Bangalore
Managers of business intelligence, analytics, big data professionals, data and database professionals adding big data analytics to their skills, recent college graduates and graduate students in related discipline looking to move into Data Science.
*A strong quantitative background with a solid understanding of basic statistics, as would be found in a statistics 101 level course.
*Experience with a scripting language, such as Java, Perl, or Python (or R). Many of the lab examples taught in the course use R (actually RStudio), which is an open source statistical tool and programming language
*Experience with SQL
At the end of Data Science and Big Data Analytics training course, participants will be able to:
*Immediately participate and contribute as a Data Science Team Member on big data and other analytics projects by
*Deploy the Data Analytics Lifecycle to address big data analytics projects
*Reframe a business challenge as an analytics challenge
*Apply appropriate analytic techniques and tools to analyze big data, create statistical models, and identify insights that can lead to actionable results
*Select appropriate data visualizations to clearly communicate analytic insights to business sponsors and analytic audiences
*Use tools such as: R and RStudio, MapReduce/Hadoop, in-database analytics, Window and MADlib functions
*Explain how advanced analytics can be leveraged to create competitive advantage and how the data scientist role and skills differ from those of a traditional business intelligence analyst
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