Programming in R

lt;pgt;This four-day course is designed for existing R users who want to extend their knowledge of the language beyond the use of existing CRAN packages. Perhaps with the aim of increasing the depth of your understanding into how different functions work, or in order to progress into developing your own algorithms and packaged software.lt;/pgt;lt;pgt;This course introduces engineering and software development concepts with practical programming exercises and covers essential topics such as the range of built-in data structures and data types, controlling the flow of a program with selection and iteration, creating your own methods and data structures, creating programs following development best practices, and assessing and improving the performance of your code.lt;/pgt;lt;pgt;You will also have the opportunity to tackle a consolidation project in which time series data is analysed with differing decision signals to simulate the past effect that a decision making strategy would have had amp;ndash; these skills and knowledge are transferable to many other simulated situations in a multitude of sectors.lt;/pgt;lt;pgt;For those wishing to certify as Data Scientists this course is aligned with many certifications and professional frameworks in order to support you on your learning journey. In particular for experienced Data Science or Data Analysts, Machine Learning Engineers, Software Developers, and those with similar responsibilities.lt;/pgt;lt;pgt;It is expected that you will have experience with R and R Studio (or another IDE) previously or experience with another programming language for Software Development. We offer many R courses and would suggest lt;a href="https://www.qa.com/QADHR"gt;lt;ugt;lt;stronggt;QADHR Data Handling with Rlt;/stronggt;lt;/ugt;lt;/agt; as a starting point for anyone not already comfortable with the base R language and Tidyverse.lt;/pgt;lt;pgt;lt;stronggt;Target Audiencelt;/stronggt;lt;/pgt;lt;pgt;This course is for individuals who have experience with Python or R in the context of a Data Science or related field.lt;/pgt;lt;ulgt;lt;ligt;Data Scientistslt;/ligt;lt;ligt;Software Developerslt;/ligt;lt;ligt;Advanced Data Analystslt;/ligt;lt;ligt;ML / AI Data Engineerslt;/ligt;lt;/ulgt;lt;pgt; lt;/pgt;