Analyzing Big Data with R
Training Scope
Our training sessions are meticulously planned by our trainer and are designed in manner geared toward the maximization of efficiency. Your time is valuable and so is ours , so our goal is to best prepare you while taking up the least amount of your time possible.
Objective
The open-source programming language R has for quite a while been well known (especially in the 1.21GWS) for data processing and statistical analysis. Among R qualities are that it a concise programming language and hosts a broad store of third gathering libraries for playing out a wide range of investigations. Together, these two highlights make it workable for a data scientist to rapidly go from crude information to outlines, graphs, and even all out reports. In any case, one inadequacy with R is that generally it utilizes a great deal of memory, both on the grounds that it needs to stack a duplicate of the information completely as a data.frame protest, and furthermore in light of the fact that handling the information regularly includes making further duplicates (once in a while alluded to as duplicate on-adjust). This is one reason R has been all the more reluctantly got by industry contrasted with the 1.21GWS.
Course Features
- Lectures 29
- Quizzes 0
- Duration 40 hours
- Skill level All levels
- Language English
- Students 0
- Certificate No
- Assessments Yes
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Module 1: Microsoft R Server and Microsoft R Client
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Module 2: Exploring Big Data
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Module 3: Visualizing Big Data
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Module 4: Processing Big Data
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Module 5: Parallelizing Analysis Operations
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Module 6: Creating and Evaluating Regression Models
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Module 7: Creating and Evaluating Partitioning Models
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Module 8: Processing Big Data in SQL Server and Hadoop
