17. February 2020 - 10:00
Goldsmiths, University of London
United KingdomLondonVirtual Classroom OR New Cross se14 6nw OR Senate House, wc1e 7hu

Introduction to R: Data Analysis and Programming (one week) - Campus or Virtual Classroom, Goldsmiths, University of London, Monday, 17. February 2020

The course is available in four formats:



Campus


Online (Virtual Classroom) with live tutoring


Clients' Office


Bespoke (Group or 1-2-1 coaching)



Max 8 participants: the sessions are interactive, with ample opportunity for practical exercises for all participants, interaction with other students, as well as personalised feedback and guidance by the tutor.



Offers:


We are pleased to offer 20% discount on all virtual classroom AIR courses running in April and May 2020 - please email email for the discount code.



Campus Courses - VAT-free: Our venues are in central London (Senate House) and in New Cross. Room details and instructions on how to get there will be emailed to you ahead of the course.


Virtual Classroom Course Information - VAT-free: Live tutoring brings all the benefits of **** to **** training and, in addition, improves skills for ‘digital’ participation. There is now an increasing need for on-line activities in all areas of life. Meetings, interviews, presentations and conferences are increasingly opting for participation and contribution via digital platforms. Therefore, ‘digital’ participation is becoming an essential skill of the 21st century.


Bespoke Course Information: Please contact us for tailor-made course options: 1-1 coaching and bespoke group training. We will adapt the course to your tailored to your interests, needs and desired outcomes.



Next available dates: at Virtual Classroom (VC), Senate House (SH) or main campus New Cross (NC)



Mon 20 - Fri 24 Apr 2020, 10:00 - 17:00 (VC) - to book select ticket option for 20 Apr 2020


Mon 15 - Fri 19 Jun 2020, 10:00 - 17:00 (VC) - to book select ticket option for 15 Jun 2020


Mon 10 - Fri 14 Aug 2020, 10:00 - 17:00 (VC) - to book select ticket option for 10 Aug 2020


Mon 02 - Fri 06 Nov 2020, 10:00 - 17:00 (NC) - to book select ticket option for 02 Nov 2020




Learn how to process and analyse data using many of R's powerful functions, install packages for additional functionality and produce high quality graphics for use in publications.



This course offers an intensive, hands-on introduction to the R statistical computing environment, focusing on practical aspects of data analysis. The programme is designed to give you as much practical experience as possible.



The course will cover the following key aspects of using R:



Data analysis, reading in data, data exploration and filtering


Vectors, arithmetic, recycling


Graphics and advanced graphics


Analysis workflow


Making your own functions


Linear modelling


Object-orientated programming


Principal component analysis



You will experience a range of teaching and learning methods, including: lectures, active participation in tutorials, practical sessions, debates and discussions. You will also receive academic guidance and feedback on your progress throughout.



Learning outcomes


By the end of this course, you will be able to read in a variety of structured and unstructured datasets. You will be able to ‘clean’ data, which contain errors or are badly entered, as well as re-structuring data to make it more useful to you. You will have applied both linear and non-linear models on a number of different datasets to help identify and quantify important relationships between variables. You will have created publication-quality visualisations that help express these relationships visually.


In your final task you will build a predictive model based on real data, concerning either: the factors that predict survival on the titanic and/or the factors that predict childhood bullying. This task will involve real world datasets that will require data cleaning, visualisation as well as data modelling, and will demonstrate your new ability to handle and gain insight from large and unfamiliar datasets.



Other clients also took:


Those interested in large-scale data analysis and in further programming training should consider Introduction to Python in Week 2. This combination will offer a competitive edge to anyone interested in analysing, managing and working with different types of data. 



Tutoring


The course is directed by Dr Will Lawrence, who completed his PhD at the department of Electronics and Computer Science at the University of Southampton, and who has a background in psychology. Will has rich experience in delivering training in both Python and R, to diverse audiences.



Visit Goldsmiths website for more information about course.  



Booking Information


As a University, we are able to offer our courses at minimum prices, and free of VAT - to make knowledge available to as wide audience as possible.


Discounts



10% when a participant enrolls for more than one of our courses (at the same time)


20% UK students


25% Members of the UK Law and Society Association (UKLSA) 


If five people register from the same institution for the same intake, the fifth place is free


Goldsmiths students, staff and alumni - email us for current discounts




Enquiries


Email: email; Phone: +44 (0)20 7078 5468.


For information on our upcoming short courses please sign up to our mailing list.



Refund policy: See AIR courses main page



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