A 5 days summer course on data analysis and visualization in R.
In this course we will learn about some basic concepts is data analysis and will learn how to make simple analyses in R. We will focus on practical programming skills in R to visualize and analyze various data sets. We will work a lot with visualization, both for exploring larger datasets and making figures. I encourage to take a look to some of the excellent online resources in advance! You can learn about the R programming language and editor at Rstudio here and here.
- Course materials are online on google drive.
- Sign up for the google group for future email communication.
- Contact: summer.course.2018.accra AT gmail.com
Please find additional information on the links below. Some of them will only be available / completed later.
- Overview and details are on the course website.
- Readings: http://bit.ly/Readings_R_DATA_ANALYSIS
- Application for the course online. [Closed]
Some details to be specified later.
| Date | Course A | Mon, Wed, Fri → Tue, Thu | 9-19 July |
|---|---|
| Date | Course B | Tue, Thu → Mon, Wed, Fri | 10-20 July |
| Time | Every other working day, 10AM-5PM (+assignments for gap days) |
| Location | Accra campus of Uni. Ghana; Bioinformatics computer lab. |
- R programming basics to explore and visualize data.
- Concepts and best practices in data analysis.
- Why programming instead of Excel?
- Data storage and data sharing
- Metadata
- Finding relationships between variables
- Summarizing
- Concepts and best practices in visualization.
- Visualization for different goals
- Showing summarized or raw data
- Scatterplots, bar plots, box plots, violin plots, strip charts, pie charts, venn diagrams, etc.
- Saturation
- Making publishable figures
- Reporting: Building entire, publishable reports from R
- Some typical applications of statistics and machine learning.
- Descriptive and inferential statistics.
- Supervised and unsupervised learning.
- <15 people.
- Combination of lectures (powerpoint/slide based) and on-hands programming in a computer lab / own laptop in R.
- The course is every other day, you will have programming assignments for the gap days.
- !!! In case we cannot get a computer lab, you need to bring your own laptop.
- If you don't have one, please contact us.
- You also need to install RStudio on your laptop before the course (it's free).
- Introduction, and links to tutorials and books will be provided here (later) if you want to brush up your knowledge on some topics.
- Course materials are online on google drive (and will remain so after the course).
- You find the source code for each day's analysis, or you can view the slides online, see examples:
(Might not display on certain browsers)
- 00.Personal.Introduction
- 01.Intro
- 02.Data
- 03.Visualisation.in.R
- 04.Statistics
- 05.Reporting.in.Markdown
- 06.Text processing
- 07.Machine Learning
- 08.Vector.and.Pixel.graphics
See photos from the B course in the course album!
<script src="https://www.publicalbum.org/js/pa-embed-player.min.js" async></script>Thanks for all your feedback on the course! I will try to improve the next course based on your feedback Please see the course evaluation results below (follow the link to results).
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