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
