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- Advanced Data Analysis using R
Advanced Data Analysis using R
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Short Overview
The statistical language R is a valuable tool for data management and statistical analysis that includes state-of-the-art data analytics related methodologies. R is an open-source language where anyone can contribute by developing libraries implementing statistical methodologies. This fact has led to a breakneck, almost frenetic, pace of development. At the same time, R has high-quality graphics making it an important tool in data visualisation. This creates an immediate need for training of many statistics graduates in this language. At the same time, the development of methodologies for the analysis of big data and the developments in both statistical science and other related sciences led to an increased need for training more data related scientists in R.
We have already successfully launched an e-learning project entitled "Data Analysis Using R". In that first introductory program, basic knowledge of R is taught to participants while the data analysis part is limited to a relatively simple level. In this second R course, we will deal with more advanced data analysis topics that are also more realistic in dealing with practical and real life problems.
One of this program's objectives is to train managers and recent graduates on how to analyze data using R while also ensuring that trainees will fully grasp key statistical principles through the use of R as a tool. In this context, this program offers ways to use R for statistical data analysis on real problems, always keeping in mind the applications and modern data management problems that occur in practice.
Learning Goals
At the end of the module, the student will know:
- Use the R language and its various libraries
- How to read data and analyze them using R and its various libraries/packages
- Be able to analyse data using appropriate statistical methods
- Know methods of statistical analysis of data and how they are used in everyday life to solve problems and manage uncertainty
- Manage data and perform appropriate pre-processing in order to structure the data in a form suitable for statistical analysis
Program Value
The program offers ways of using R for statistical analysis of data in real problems, always keeping in mind applications and modern data management problems that occur in practice.
Evaluation Method And Final Grade Computation
Assessment is based on an assignent (the trainee submits an extensive data analysis task using R using real data) and quiz submission in each module. Successful completion of the program and conferral of the training certificate requires a final grade of at least 50%.
Learning Method Description
The program uses the eLearning educational method: learning takes place purely asynchronously (that is, on days and hours that serve the trainee, without mandatory attendance at a specific time or day), exclusively remotely (using a special educational platform via the internet from the trainee's area) and using digital educational tools that ensure effective and flexible individual self-learning. The program's training material becomes available at specific time periods, based on the training path followed, and then remains available on the training platform without restrictions throughout the duration of the program.
Teaching Language
English
Application deadline: 16/10/2024
Program start: 23/10/2024
Program completion: 19/01/2025
Scientific area
Way to follow
ECTS units: 5
Hours of asynchronous training: 75
Includes training hours (indicative) using an asynchronous distance learning (eLearning) platform.
Includes training hours (indicative) using an asynchronous distance learning (eLearning) platform.
Additional hours of employment: 75
Additional hours of work are included (indicative) and may include individual study, writing assignments, participation in field visits, participation in exams, etc.
Additional hours of work are included (indicative) and may include individual study, writing assignments, participation in field visits, participation in exams, etc.
Total hours: 150
The total hours include hours of synchronous and asynchronous training, as well as additional hours of employment.
The total hours include hours of synchronous and asynchronous training, as well as additional hours of employment.
Weeks of training: 12
Weeks in which activities of any kind are planned are included.
Weeks in which activities of any kind are planned are included.
Vocational Education and Training Certificate
Trainees who successfully complete the program are granted a Vocational Education and Training Certificate of the Center for Education and Lifelong Learning of the Athens University of Economics and Business, which is accompanied by a Supplement to the Certificate, detailing the subject of the program, the thematic units attended by the trainee , as well as the training methodology followed.
Target Audience
- Students of statistics or related departments who want to learn the R language.
- Graduates of Statistics departments from previous years where R was not taught.
- Graduates of Statistics departments from recent years who either were not taught R or would like to delve deeper.
- Graduates of Mathematics departments who, while having been taught theoretical courses, have little familiarity with the use of statistical programs such as R.
- People who are already working and in their daily lives need to analyze data and use R.
- Researchers from various other subjects who need both statistical methods and the use of R for their research.
- Scientists with basic knowledge of statistics who want to delve into more advanced methods.
- Researchers who want to learn modern methods of data analysis.
Prerequisite Knowledge
- A prior knowledge of statistics (to have successfully taught, for example, a course).
- Basic computer skills (word processing, worksheets, browsers, e-mail)
- Knowledge of English at the B2 level as a minimum.
- Basic knowledge of R. In case the trainee has no previous knowledge of R but has been taught the basic concepts of statistics, then it is recommended to first successfully attend the program "Data Analysis using R".
Scientific Responsible
Program Tutors
Mode And Frequency Of Communication
Communication between trainers and trainees is mainly asynchronous, through e-mails and/or personal messages through the training platform. However, a limited number of teleconferences are planned, to resolve questions and related issues.
Cost
ELEARNING: 400€
Installements
The total amount of tuition is €400 and is paid in two installments. The first installment, of €180, is paid as an advance payment before the start of the courses, to secure the place, and the second, of €220, is paid before the program is half completed. In the event of a discount, the above amounts are reduced proportionally. Especially in the case of a 20% discount, the above amounts are set at €320 (total amount), €180 (first installment - ??advance payment) and €140 (second installment).
Trainees are informed of the installment amounts and related deadlines via email upon their acceptance into the program.
CONTACT
46, Kefallinias Str., 11251, Athens
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dummy kedivim-opa@aueb.gr
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dummy+30 210 8203 912
For the in Class programs:
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dummydz@aueb.gr
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dummy+30 210 8203 916, 912, 914
For the eLearning Programs:
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dummyelearning@diaviou.aueb.gr
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dummy+30 210 8203 753
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