Problem Solving Using Open-Source Languages; R and Python

This hybrid course is structured as follows:

• Introduction to R and Python
• Data Manipulation and Visualization
• Statistical Analysis and Machine Learning
• Final Project The participants will earn 3 ECTS. The final Project will be completed at University of Novi Sad.

Content and Methodology

In the initial week, participants will acquire introduction to the R and Python programming languages, encompassing the setup of the environment, basic syntax, data types, as well as fundamental data manipulation and analysis.

Moving on to the second week, the learning objectives will revolve around data input/output, employing dplyr in R and pandas in Python for data manipulation, and utilizing ggplot2 in R as well as matplotlib/seaborn in Python for data visualization.

The focus of the third week will shift towards statistical analysis using R and Python, accompanied by an introduction to machine learning. Supervised learning algorithms, including linear regression, logistic regression, decision trees, and random forests, will be introduced.

In the concluding phase, the final project will require students to engage in a practical application of their acquired skills and concepts. This project will involve working with R and/or Python to demonstrate proficiency in the tools and methodologies learned throughout the course.

The online part will take place on the 1st, 2nd, 8th, 9th, 15th and 16th of October from 8:30 to 15:30, and the onsite part will take place on the 25th and 26th of October.

Upon completion of a course on Problem Solving Using Open-Source Languages R and Python, learners can expect to achieve the following learning outcomes:

• Proficiency in programming with both R and Python and the ability to solve problems in both languages.
• Ability to perform data manipulation and visualization tasks using the respective tools/packages of R and Python.
• Understanding of basic statistical concepts and ability to analyze data using statistical techniques in both R and Python.
• Familiarity with the principles of machine learning, its algorithms, and its application in both R and Python.
• Ability to think critically and creatively to solve real-world problems using R and/or Python.
• Ability to work collaboratively and communicate effectively in a team to complete a final project that applies concepts learned in the course.

Competences

• Digital skills
• Critical thinking
• Creativity & problem solving

Requirements

• Selection strategy: Previous knowledge is not required. The learners interested in critically and creatively solving real-world problems using R and/or Python should apply. The selection strategy is based on goals and objectives for taking the course as well as specific needs and areas of interest related to R and Python software, which will be described in a motivation letter (required). Another selection critera is diversity in order to create a diverse group of participants, including those from different backgrounds, industries, and levels of experience, to promote learning and collaboration among participants. .
• Number of participants: 20.
• Certificate/ECTS: 3 ECTS.
• Language: English.

Please note that the participants will get a scholarship for travel and subsistence. The participants will be contacted by the EUGLOH team at their home university to get more information.

This activity is part of WP2