Data analysis in R (ONLINE LIVE TRAINING)

BeginnersUpdated

The R programming language is one of the leading languages in the field of data science. It’s widely used for data visualisation, analyses, statistics and machine learning.

It is open-source software and all the software we use during the course is free. This course is aimed to provide an introduction to R, focussing on exploratory data analysis and visualisation. By the end of this course you will be able to read in, analyse, interpret and visualise data.

If you do not have a University of Cambridge Raven account please book or register your interest here.

If for any reason the above links do not work, please email Research Informatics Training Team with details of your course enquiry.

• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Research Informatics Training Team.
• Further details regarding eligibility criteria are available here.

• This course is open to everyone who is interested. Have a look at our relevant guidelines.

The course is aimed at beginners, so no prior knowledge is required. If you already have some coding experience, but look to refresh your knowledge, this course is also for you. Different exercise levels will help challenge you at the appropriate level.

• Get familiar with the programming language.
• Be able to use appropriate interface software.
• Be familiar with different data types & structures and know when to use them.
• Read in and investigate tabular data and perform basic quality control checks.
• Create plots and be able to manipulate plot aesthetics.
• Feel confident manipulating columns (variables in the data) and rows (observations in the data).
• Perform operations on groups within your data.
• Reshape data (long <> wide) and know when each format is appropriate.
• Combine different tables of data, based on a common identifier.
• Clean up common issues in data (column names, encoding issues etc).
• Fine-tune plot settings to create publication-ready figures.

The course combines short presentations and demonstrations with lots of hands-on practice. This is delivered through slides, live-coding and dedicated online practical materials.

Participants must have their own computers to work on and a stable internet connection for the duration of the course.

The course is split into 4 half-day sessions, that build upon knowledge gained in the previous ones. Depending on the scheduling, these sessions can take place consecutively (2 sessions in a single day) or as half-days.

• Free for registered University of Cambridge students
• £ 65/full day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 65/full day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 130/full day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

2 days (4 half-day sessions)

several times a year

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