Data Science with R (Class Room)
Today almost all sectors have access to more data than they can decipher. And every day a new technology is created to organize and make sense of this avalanche. Still, businesses have not been able to solve this puzzle, they are constantly trying to derive value and see how they can use data more effectively—not just their own data, but also data out there that is relevant to what they do.
This inability is due to lack of expertise. Working with incomplete, unstructured data that might often need to be combined with other data to be made useful, requires certain distinctive new skills. Also, there is the concern of privacy, security, and ethics.
The field of data science is developing and the need for associated skills is increasing.
- Interactive classes
- Our trainers have over 12–15 years of relevant industry experience.
- End-to-end Data Handling with R (Read, write, control structure/functions).
- Access to our cloud server for testing.
- Hands-on training in a real-time project environment to give you maximum benefit.
- Weekend mentoring discussions with our technical architects.
- Quality assurance: if you are not satisfied, you can attend our next session with a different trainer for free!!
- Step-by-step approach to enable you to achieve highly recognized certifications such as Cloudera.
- Life-time access to the learning management systems (LMS).
- Technical support (via email) for assignments, queries.
- Batch rescheduling flexibility! Incase you miss a class… fret not! You can join the next batch.
- Sources of data.
- Acquiring and evaluating data.
- Transforming Data into useful formats.
- Statistical methods and relationships.
- Linear regression and logistic regression.
- Hypothesis analysis, correlation and co-variance.
- Plots, correlation, subsets, observations, transformations.
- Collinearity and different types of regressions.
- Data Forecasting Techniques.
- Introduction to ‘R’ and basic functions.
- R studio.
- Data sets.
- Operators and scripts.
- Data types, frames and exercises.
- Export and import of excel files.
- Object creation.
- Lists, functions, conditions, iterative statements and graphs.
- Hadoop overview.
- Data storage mechanisms.
- Pig: features, uses and cases.
- Using Pig (loading data, field definitions, schema, filter, sort, functions).
- Data sets management.
- Machine learning basics.
- Apache mahout and sample experiments
- 3 Days
- March 18th, 19th and 20th 2017
- April 16th, 17th and 18th 2017
- May 18th, 19th and 20th 2017
- June 18th, 19th and 20th 2017
- Chicago, San Francisco, Newyork city, Washington D.C
An individual keen to pursue this course must have basic knowledge of Apache Hadoop, HDFS, MapReduce, Hive and Hadoop steaming. Along with the above mentioned skills he/she must also know Python, Perl or Ruby or any other scripting language.
With Data becoming the crux of all matters economic, the demand for data-savvy professionals has grown. However, the supply of these skilled experts is limited.
A recent study by the McKinsey Global Institute concludes, “a shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge (for the U.S.).” The report quotes that there will be over four to five million jobs in the US requiring data analysis skills by 2018.
Today, businesses are willing to pay a hefty salary for data engineers, scientists, statisticians, and analysts. With our Data Science with R, we at Netscientium are here to provide you with the right training, guidance, research and professional skills to succeed in this cutting edge market.
Looking to Develop your Data Science Skills?
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