Instructor: Alexandra Gemitzi
Lesson Code: 15ΑΥ4Ν
Semester: 1st
Weekly teaching hours: 2 Theory / 1 Laboratory courses
Prerequisites: No
Course offered to Erasmus students: No
Course URL: TMC340/

Learning Outcomes: 

Please describe the learning outcomes of the course: Knowledge, skills and abilities acquired after the successful completion of the course:

• Understanding computer data processing
• Familiarization with algorithms
• Understanding the way mathematical problems are handled within R
• Customized programming for environmental engineers
• Improvement of computer programming skills
• Acquisition of using open programming package R

Course Content: 
1. Information handling. The binary system.
2. Algorithms and flow charts.
3. Introduction to R programming.
4. The R Studio platform
5. Data objects: vectors, array
6. Data objects: lists, factors, data frames.
7. Functions in R
8. Mathematical computations in R: mathematical operations, simple functions, operations with vectors and arrays
9. Linear systems of equations, random numbers, other useful functions.
10. Graphics: the ggplot package
11. Linear regression analysis
12. Multivariate linear regression analysis
13. The R Shiny web apps development environment

Suggested Bibliography: 
An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics Version 3.3.1 (2016-06-21) by W. N. Venables, D. M. Smith and the R Core Team,

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