Big Data Mini Camp | R Programming Basics for Data Science
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 the analyst has a statistical, numerical, or probabilities-based problem based on real data and they've pushed Excel past its limits.
R Programming for Data Scientists & Analysts is a comprehensive hands-on course that presents common scenarios encountered in analysis and present practical solutions. In this course, special attention is paid to data science theory including AI grouping theory. A discussion of using R with AI libraries like Madlib are included.
Course Objectives: What You’ll Learn
This course provides indoctrination in the practical use of the umbrella of technologies that are on the leading edge of data science development focused on R and related tools. Working in a hands-on learning environment, led by our expert practitioner, students will learn R and its ecosystem, and where it’s a better a tool than Excel
- 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 (overview)
1. From Excel or SAS to R (Optional)
- Common challenges with Excel / SAS
- The R Environment
- Hello, R
2. Working with R Studio
3. R Basics
- Simple Math with R
- Working with Vectors
- Comments and Code Structure
- Using Packages
- Vector Properties
- Creating, Combining, and Iteratorating
- Passing and Returning Vectors in Functions
- Logical Vectors
5. Reading and Writing
- Text Manipulation
- Working with Dates
- Date Formats and formatting
- Time Manipulation and Operations
7. Multiple Dimensions
- Adding a second dimension
- Indices and named rows and columns in a Matrix
- Matrix calculation
- n-Dimensional Arrays
- Data Frames
8. R in Data Science
- AI Grouping Theory
- Linear Regression
- Logistic Regression
- Elastic Net
9. R with MadLib
- Importing and Exporting static Data (CSV, Excel)
- Using Libraries with CRAN
- K-means with Madlib
- Regression with Madlib
- Other libraries
10. Data Visualization
- Powerful Data through Visualization: Communicating the Message
- Techniques in Data Visualization
- Data Visualization Tools
11. Databases, Data lakes & 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. Specifically, R sprint, paste, paste0, and paste3 (not sure of the equivalent in Python).
Optional - Time Permitting Topics
12. 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
13. Business Rule Systems
- Rule Systems in the Enterprise
- Enterprise Service Busses
- Using R with Drools
14. R with AWS
- Best practices for working with AWS (completely outside of R and Python)
Course delivery details
Student Materials: Each student will receive a Student Guide with course notes, code samples, software tutorials, diagrams and related reference materials and links (as applicable). Our courses also include step by step hands-on lab instructions and and solutions, clearly illustrated for users to complete hands-on work in class, and to revisit to review or refresh skills at any time. Students will also receive the project files (or code, if applicable) and solutions required for the hands-on work.
Classroom Setup Made Simple: Our goal is to make getting access to hands-on training as painless as possible. We offer several flexible options to help meet your team's equipment and set up needs. Our dedicated tech team will work with you to ensure your classroom is ready to go, ensuring a smooth start to class and hands-on experience for your students.
- Have your own student machines? Manual Setup Made Simple. Every course includes a detailed Course Setup Guide that details classroom and student machine system requirements, download links for course software and student lab files, and detailed instructions for installing, testing (and eventually removing) the course software and labs. Our tech support team is ready to help you every step of the way to get your firm installed and ready for class.
- Need Hands-on Software Access?We can provide a complete LoadNGo™ Course Package (or image) or host the labs on our Remote / Cloud-based Lab Server. If you have student machines, but need access to the software or lab environment, we can set up all the course items on our remote hosted lab server. Students can login to our server from their machines to perform the hands-on work. For some courses, we can also supply a course image with complete installation running on a virtual machine. Additional costs may apply - please ask for details.
- Need a Complete EquipmentSolution? We can supply Pre-Loaded Equipment. If you need student machines, we can send in equipment, right to your facility, pre-loaded and ready to go. Additional costs may apply - please ask for details.
- Price: $1,895.00
- Discounted Price: $1,231.75
Why choose Trivera Technologies LLC?
Over 25 years of technology training expertise.
Robust portfolio of over 1,000 leading edge technology courses.
Guaranteed to run courses and flexible learning options.
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Trivera Technologies is a IT education services & courseware firm that offers a range of wide professional technical education services including: end to end IT training development and delivery, skills-based mentoring programs,new hire training and re-skilling services, courseware licensing and...