Introduction to R for Data Analytics
Neformālās izglītības programma "Introduction to R for Data Analytics"
Informācija par kursu
R is established as one of leading programming languages for data analytics. Today R is a tool of choice for many professionals in different industries. This introduction to R course will help you to start working in R environment and obtain a solid background for further progress in data analytics. The course starts from the basic syntax of R commands and lead you to your first data analysis in R.
The course is organized as a continuous practicing of your newly acquired skills.
Aim of the course
The course is designed to provide a quick and efficient introduction to R environment and develop participants’ practical R programming skills. The course is best suited for:
- Software developers, who want to dive into the data science
- Statisticians and data analytics, who want to get acquainted with R
- Computer proficiency
- Programming experience (any language) is highly recommended
- Background in statistics is beneficial, but not required
- Obtain practical skills of R programming
- Apply core techniques of data processing
- Use R for data visualization
- Run classical models and present the results
|Programmas ilgums: Tuesdays, Thursdays, from 18:00 till 21:00(16 academic hours, 4 evening sessions 4 academic hours each)|
|Apguves valoda: English|
|Sākums: 18 Februāris, 2020*|
*Kursa sākuma datums var mainīties, ja grupa netiks nokomplektēta
|Pasniedzējs: Dmitry Pavlyuk, Dr.sc.ing|
|Kursu cena||Maksāt 220 EUR|
|TSI studentiem un Alumni||Maksāt 200 EUR|
[SVARĪGI] Pirms apmaksas veikšanas, pārliecinieties vai grupa ir nokomplektēta.
Session 1. Basics of R programming
- How it works (introduction to R console and RStudio)
- Coding basics and variable types in R
- Installing third-party packages
- Vectors and lists
- Basic programming structures (conditions, loops, functions)
Session 2. Handling data
- Data frames
- Importing data
- Data pipes (tidyverse library)
- Managing data (arranging, filtering, summarizing)
- Descriptive statistics and grouped summaries
Session 3. R visualization tools
- Basic plots (charts, scatters, histograms)
- ggplot2 library
- Aesthetic mappings
- 2D and 3D plots
- Plotting spatial data
Session 4. Basic data analytics in R
- Model basics
- Model building
- Running and understanding basic models
- Visualizing models and their results
Postdoctoral researcher; assistant professor; head of TSI mathematical methods and modelling department. Dmitry holds two doctoral degrees – in economics and in engineering and has17 years of high school teaching experience.
Dmitry is an active researcher in the sphere of data analytics and a highly experienced R developer, the author of two R packages, accepted in the official Comprehensive R Archive Network (CRAN).
Reģistrācija ir obligāta!
email@example.com, Transporta un sakaru institūts, Lomonosova iela 1 – 404.kab., Rīga, LV-1019, Latvija, tālrunis: (+371) 67100652