R Programming for Data Scientists and Analysts
R Programming for Data Scientists and Analysts Course Details:
R is a functional programming environment for business analysts and data scientists. It's a language that many non-programmers can easily work with, naturally extending a skill set that is common to high-end Excel users. It's the perfect tool for when you have a statistical, numerical, or probabilities problems based on real data and you’ve pushed Excel past its limits.
This comprehensive hands-on course presents common scenarios encountered in analysis and shares practical solutions. Special attention is paid to data science theory including AI grouping theory. A discussion of using R with AI libraries like MADlib is included.
Call (919) 283-1653 to get a class scheduled online or in your area!
From Excel or SAS to R
- Common challenges with Excel/SAS
- The R Environment
- Hello, R
Working with R Studio
- Rshiny
- Rpresentations
- Rmarkdown
R Basics
- Simple Math with R
- Working with Vectors
- Functions
- Comments and Code Structure
- Using Packages
Vectors
- Vector Properties
- Creating, Combining, and Iterating
- Passing and Returning Vectors in Functions
- Logical Vectors
Reading and Writing
- Text Manipulation
- Factors
Dates
- Working with Dates
- Date Formats and formatting
- Time Manipulation and Operations
Multiple Dimensions
- Adding a second dimension
- Indices and named rows and columns in a Matrix
- Matrix calculation
- n-Dimensional Arrays
- Data Frames
- Lists
R in Data Science
- AI Grouping Theory
- K-means
- Linear Regression
- Logistic Regression
- Elastic Net
R with MADLib
Importing and Exporting static Data (CSV and Excel)
Using Libraries with CRAN
K-means with MADlib
Regression with MADlib
Other libraries
Data Visualization
- Powerful Data through Visualization: Communicating the Message
- Techniques in Data Visualization
- Data Visualization Tools
- Examples
Databases, Data lakes, and additional Topics
- Building connections to Databases and Data lakes, for both Python and R (using Hive server)
- Methods to “query” data from database and data lakes, for both Python and R
- Creating and passing macro variables.
R with Hadoop
- Overview of Hadoop
- Overview of Distributed Databases
- Overview of Pig
- Overview of Mahout
- Exploiting Hadoop clusters with R
- Hadoop, Mahout, and R
Business Rule Systems
- Rule Systems in the Enterprise
- Enterprise Service Busses
- Drools
- Using R with Drools
*Please Note: Course Outline is subject to change without notice. Exact course outline will be provided at time of registration.
Join an engaging hands-on learning environment, where you’ll learn:
- R Language and Mathematics
- How to work with R Vectors
- How to read and write data from files, and how to categorize data in factors
- How to work with Dates and perform Date math
- How to work with multiple dimensions and DataFrame essentials
- Essential Data Science and how to use R with it
- Visualization in R
- How R can be used in Spark
This course has a 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work.
Before attending this course, you should have:
- Experience working with Excel or SAS
- Understand SQL basics
Data Scientist, Data Analyst, Data Architect, Statistician, Data Engineer, Developer, and Database Administrators who need to leverage R for analytics.