Business Analytic with R Programming

Course length:

Five full days (eight hours each)

Course goals:

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment, discuss generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.

Target audience:

Individuals with programing and statistics expertise who wins to learn the basics of programming in R.

Course Methodology: Five daily sessions of about eight hours each. This is the general daily schedule:

  • 09:00-10:30 First session
  • 10:30-10:45 Recess
  • 10:45-12:00 Second session
  • 12:00-13:00 Lunch break
  • 13:00-15:00 Third Session
  • 15:00-15:15 Recess
  • 15:15-17:00 Fourth Session

We believe that only practical hands on experience will help fully understand the material at hand. For this reason, each session includes a practical exercise where the actual hands on experience can be gained.

Content:

Day 1 – Overview of R, R data types and objects, reading and writing data

  • Overview and History of R
  • Getting Help
  • Data Types
  • Subsetting
  • Vectorized Operations
  • Reading and Writing Data Part 1
  • Reading and Writing Data Part 2
Day 2 – Control structures, functions, scoping rules, dates and times
  • Control Structures
  • Functions
  • Lapply
  • Tapply
  • Split
  • Mapply
  • Apply
  • Coding Standards
  • Dates and Times

Day 3 – Loop functions, debugging tools

  • Scoping Rules
  • Debugging Tools

Day 4 – Simulation, code profilingES6, TypeScript, Angular-CLI and Angular Components

  • Simulation
  • R Profiler

Lokasi Training

IT Learning Center
Permata Kuningan bld 17th floor, Jl. Kuningan Mulia Kav. 9
HR. Rasuna Said, Jakarta Selatan – Indonesia

Hubungi kami untuk informasi lebih detail

Jakarta

Jakarta
Email : [email protected]
Phone/WA : 0811-1798-352

Surabaya
Email : [email protected]
Phone/WA : 0811 1798 349

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