This one-week hands-on course will teach you how to use R for data analysis and programming. It covers data manipulation, statistical analysis, and programming basics; and introduces some more advanced programming concepts.
This course is part of the rich portfolio of AIR Programming, AI and Data Science courses, available on Zoom, on campus and at clients’ offices, with options for training at all levels – both for individuals and businesses.
Key features of this R course
As with all other AIR Courses, this course is taught in small groups in a relaxed environment by expert instructors who will guide you every step of the way. The course is designed for those who have little to no prior programming experience. You don't need to worry about feeling left behind.
Throughout this course, you'll get to work on a data manipulation project using R. On your final day, you'll build a predictive model based on real data about the factors that predict survival on the Titanic and/or the factors that predict childhood bullying. This will involve real datasets that require you to use different skills you've learnt throughout the week, to demonstrate your ability to handle and gain insight from large and unfamiliar datasets. This is a great opportunity to put your new skills into practice and learn through hands-on experience.
By the end of the course, you'll have a solid understanding of R programming basics and be able to use R for advanced data analysis.
Overall, if you would like to learn how to program with R, and a small-group interactive setting is suitable for you, then this one-week interactive course is perfect for you.
Join us now and enhance your programming and data analysis skills in a short period of time!
During the course, you'll cover the following topics:
- Introduction to R programming language
- Overview of R's practical applications.
- Industries that use R and demand for R skills.
- Benefits of learning R.
- Programming concepts and principles
- Basic syntax, variables, and data types.
- Loop and control flow structures (for-loops, if-statements).
- Data analysis and manipulation
- Reading in data, data exploration and filtering.
- Vectors and arithmetic.
- Basic and advanced graphics.
- Analysis workflow.
- Creating your own functions.
- Linear modeling.
- Real-world application and project
- Building a predictive model based on real data.
- Handling large and unfamiliar datasets.
- Feedback and guidance from instructors.
- Communication and presentation skills
- Creating publication-quality graphics.
- Communicating insights to non-technical stakeholders.
- Cleaning and preparing datasets for analysis.
Bespoke content to suit different levels and industries is available on request.
By the end of this course, you'll:
- Understand the basic principles and concepts of programming in R.
- Learn R syntax, variables, and data types.
- Understand loop and control flow structures (for-loops, if-statements) in R.
- Learn how to analyse and filter data in R.
- Learn how to create basic and advanced graphics in R.
- Understand the analysis workflow in R.
- Learn how to create and use functions in R.
- Understand linear modeling in R.
- Apply R's fundamental techniques to real-world scenarios.
- Create publication-quality graphics to communicate insights to stakeholders.
- Read and clean various types of datasets to make them more useful for analysis.
- Develop the confidence to continue building R skills independently.
- Apply R knowledge in a real-world context.
- Receive a certificate of completion to demonstrate R skills to potential employers or clients.
Bespoke courses and group bookings
We regularly provide bespoke training for small and large groups. If you are interested in a tailor-made R or another Programming course, please email us air (@gold.ac.uk).
A solid investment
The numerous applications of R programming make R a go-to tool for data scientists, analysts, and programmers across various industries. R applications include data and statistical analysis, computer modeling, and graphics. R is equipped with a vast range of built-in functions and packages for statistical analysis, machine learning, and data visualisation.
This means that R is used across industries, such as banking and finance, healthcare, e-commerce, social media, and manufacturing – making R skills impactful for employability and career progression across industries.
In addition, by investing in R programming, you can learn the skills necessary to extract insights from data and make data-driven decisions, which can be advantageous to both personal and professional pursuits.
As an open-source programming language, R is free to use and has a large and active community of developers. By investing in R programming, you can leverage the work that others have already done, instead of building everything from scratch. This can save you time and resources, making your projects more efficient.
R makes it easy to document and reproduce your work, which is critical in fields like science and engineering, where results must be validated and replicated. By investing in R programming, you can ensure that your work is transparent and reproducible, increasing its impact and credibility.
Why study programming at Goldsmiths
Our courses stand out for several reasons. Highly experienced tutors teach you in small groups, enabling interactive learning and fast progress. This small-group interactive format is preserved for large bookings (e.g. for hundreds of employees).
By choosing our courses, you'll also be supporting education and research, as 100% of our income beyond operational expenses is used towards these goals.
Goldsmiths is a top-tier educational institution in terms of social mobility and academic reputation. Learn more about our commitment to education and research.
The one-week R course is designed to equip you with a solid foundation of R programming and data analysis. If you wish to further develop your programming and data analysis skills, then you can choose from the following courses or get in touch for bespoke training. We offer tailored training at all levels. If you would like us to help you with choosing the most suitable option for you, please feel free to contact us.
Related courses include:
- Introduction to Machine Learning with R
- Machine Learning, Artificial Intelligence and its Application to Industry
- Browse our full range of AIR programming courses.
Please note our short courses sell out quickly, so early booking is advisable.
Find out more about all of the AIR courses available to you.
For all enquiries, and to be regularly updated on upcoming AIR courses, please email: air (@gold.ac.uk). For anything urgent, or if emailing is not a good option for you, you can also call us via WhatsApp or phone on +44 (0)7908 566 949.
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Short courses mailing list: for information about our upcoming short courses please sign up to our mailing list.
Discounts, location, and more dates
We offer several discounts, as well as sponsorships. 'Format' is date-specific – this and other AIR courses are available on campus, via a digital platform (e.g., Zoom), and at your offices. Additional dates are also available. Please select 'Book now' to find out more.
We are committed to providing reasonable teaching adjustments for students with disabilities that may impact on their learning experience. If you require adjustments, please complete the relevant section on the booking form and also contact us at email@example.com so we can respond to your requests as soon as possible.
Please note our short courses sell out quickly, so early booking is advisable.
The course is supervised by Carlos Salas Najera, who has more than 15 years of experience in investments, data science and machine learning. Carlos has a BSc in Economics, MSc in Finance as well as postgraduate education in Data Science and Machine Learning at the New York City Data Science Academy. He is a holder of the CFA and CQF professional investment certificates. Carlos is an FCA-regulated C30 investment professional whose career spans investment firms such as Santander AM, BNP Paribas AM, LCAM and Jefferies International. In addition, Carlos is also deeply committed to education and research initiatives. He leads the CFA Machine Learning Working Group; and has advised the IFRS Foundation on new accounting standards.