General Course options Class schedule Programme Practical How to apply? Looking for a way to process your scientific information more effectively? Then this R programming course is just for you! In today's data-driven world, the ability to analyze and visualize data is essential for effectively processing scientific information. R is a programming language that has become a popular choice for statistical computation and visualization, particularly in the fields of bioinformatics and data science due to its broad applicability. This comprehensive course is designed to provide you with a solid understanding of the different data types and structures used in R. You will learn how to apply these concepts to perform data analysis, as well as how to install and use additional packages that can enhance your analysis capabilities. The course covers topics such as descriptive analysis and reporting through RMarkdown, and also includes instruction on how to build an interactive application using a Shiny app. By the end of this course, you will have gained valuable skills that can be applied to a wide range of data analysis tasks. This course is designed for those who have already basic digital skills and want to learn how to critically process and visualize scientific data. No prior programming knowledge is required. R is an open-source language, meaning it is free to use and has a large community of developers constantly creating new tools and packages to improve its functionality. Other similar tools or software often require a commercial (expensive) license. R has powerful data analysis and visualization capabilities, including a wide range of statistical and graphical tools that can help you gain insights into your data. Learning R can enhance your job opportunities, particularly in fields where data analysis and visualization skills are in high demand. Overall, learning R can be a valuable skill for anyone looking to work with data, regardless of their field of study or work. How can I participate in the course? The training is offered in two different ways: as a daytime course during office hours and through distance learning.The course content and competencies are the same in both variants; only the organization differs. With the exception of the exam in the daytime course variant, the training can be entirely completed remotely. Daytime education - on campus, from home, or a combination of both Period: February - April 2025Duration: 6 weeksAcademic Year 2024-2025Weekly Schedule: 8 hours of class per week, divided into 2 sessions of 4 hours each on 2 different daysDepending on your schedule, you can choose to attend some classes on campus and others online:On campus: You participate in classes alongside students of the Advanced Bachelor of Bioinformatics program.From home: Classes held on campus can also be attended online via live streaming, from the comfort of your own home.Unable to attend? All classes will be recorded and can be viewed or reviewed later.The exam is scheduled on campus in Bruges, Belgium, during office hours. Distance education - self-study, supported by evening classes, on campus or from home Period: October - December 2025Duration: 6 weeksAcademic Year 2025-2026Study Approach:You will study the material through self-study, with study materials provided along with necessary explanations for independent processing.Additionally, we provide recordings of daytime classes as supplementary resources.Contact Sessions: There are three scheduled contact sessions every two weeks, held on campus from 18:00 to 20:00. These sessions can also be attended remotely via live streaming and will be recorded for review.The exam is scheduled to take place in the evening, from 18:00 to 21:00, on the campus in Bruges, Belgium. However, it can also be taken from home for an additional fee. Course Organization - Daytime Education View the contents per week:WeekContact Hours (CH)Content14 CH lecture4 CH practical sessionInstallation of R and RStudio Introduction R: theoryIntroduction R: exercises24 CH lecture4 CH practical sessionData analysis and visualisation: theoryData analysis and visualisation: exercises34 CH lecture4 CH practical sessionData analysis and visualisation: theoryOther packages: package dependency (renv), ggplot, databases: theoryData analysis and visualisation: exercisesOther packages: package dependency (renv), ggplot, databases: exercises44 CH lecture4 CH practical sessionRmarkdown and ShinyExercises + introduction project assignment54 CH lecture4 CH project based learningStatistical testingProject “Data analysis and visualization of a publicly available dataset”64 CH practical session4 CH project based learningStatistical testingProject “Data analysis and visualization of a publicly available dataset”EXAM4 CHExamWhere and when the classes take place can be found in the class schedule. Additional explanation about the learning environment and class schedule will be provided via email a few days before the start of the classes. Course Organization - Distance Education View the contents per week:WeekContact Hours (CH)Content12 CH study guidanceBasics of R, data analysis and visualization32 CH study guidanceOther packages (renv, ggplot2, databases), RMarkdown & Shiny, project assignment52 CH study guidanceStatistical testingEXAM3 CHExamWhere and when the classes take place can be found in the class schedule. A few days before the start of the classes, additional explanation about the learning environment and class schedule will be provided via email. The link to the live streaming will be announced through the learning environment. Learning outcomes Knowledge of the different data types and structures in R.Apply different data types and structures in R.Select and apply the correct visualization technique for graphical representation of variables in a dataset.Search, install, test and apply R and Bioconductor packages.Conduct data manipulations on data sets and write R code to solve a problem.Apply the basic knowledge about statistics and execute a descriptive statistical analysis to evaluate biological and biomedical data sets.Apply the different statistical tests for analyzing one or more variables in a dataset and report the statistical results in a brief and scientifically approved manner. Dates and locations The microdegree in R through daytime education takes place during the period February - April 2025 of the academic year 2024-2025. Registration for this program is possible from July 1, 2024, until early February 2025. Pre-registration is already available via https://webreg.howest.be. The classes will be held on campus in Bruges, Belgium, but can also be attended from home via live streaming. The exam will take place on campus in Bruges.The microdegree in R through distance education takes place during the period October - December 2025 of the academic year 2025-2026. Pre-registration is possible starting from March 2025. The contact sessions can be attended on campus in Bruges, Belgium, or via live streaming from home. The exam will be held on campus or can be taken from home for an additional fee. Study LoadThe microdegree in R for Data Analysis and Visualization has a workload of 5 credits (ECTS). One ECTS corresponds to a study time of 25 to 30 hours.To successfully complete the program, you should consider the following (estimated) time commitment:Daytime Education: In addition to attending classes (8 hours/week), you should allocate time in the evenings or weekends to review and process the course material. During classes (week 4 to 6), time is allocated to work on assignments. Prior to the exam, you should set aside time for studying.Distance Education: Generally, you will need at least one evening and one full day on the weekend per week to independently go through the course material. Prior to the exam, you should allocate time for studying. Tuition FeesThe tuition fee for the academic year 2024-2025 is €357.00 or €1518.00 for non-EEA students (subject to change). There are no additional fees for study materials or software. The program requires a good laptop. SME PortfolioThis program is eligible for support through the SME Portfolio under the topic of profession-specific competencies. Enrolment Enrolment for the 2023-2024 academic year starts 1 July 2023. You can enrol at one of the Info Days on campus, by appointment at the student secretariat of the Howest campus where your programme takes place, or by using the online registration system. Which documents will you need? A copy of your ID (front and back) will be requested during online enrolment. You will also need to upload a copy of your (higher education) diploma. Online enrolment Open your online application check that all the necessary documents have been uploaded. Are all your documents are in order? Now you can put your study programme together and sign it. After you've registered After completing the online application, you will receive an e-mail with all the information needed to complete your enrolment. Once your file has been checked and processed by Howest, you will receive your contract and the request for payment of tuition fees and extra study costs electronically. FAQ Can't find what you're looking for, or do you have a specific question about this course? Don't hesitate to contact us. We would love to help you further. Jasper Decuyper Contact person Ask your question What is the difference between the daytime course and the distance learning course? Both variants cover the same course content but are organized differently. The day course takes place on campus in Bruges, Belgium, and occupies two half-days per week over a six-week period. Presence on campus is not mandatory, as the classes can also be attended online. In the @home course, the material is mainly processed through self-study. Over a six-week period, there are only a limited number of contact moments (three in total) that take place in the evening. Is there an evaluation associated with this micro degree? Yes, the course includes an assignment (25% of the final grade) and an exam (75% of the final grade). Those who pass the course (with a score of 10 or more out of 20) will receive a credit certificate. Will I receive a diploma after completing this micro degree? After successfully completing the micro degree and passing the exam, you will receive a credit certificate for this course. With the credit certificate, you can apply for an exemption from the course unit “Data analysis, visualization and biostatistics using R” of the Advanced Bachelor of Bioinformatics and Advanced Bachelor of Bioinformatics at home programs.