This two day introduction to R focuses on getting started with common data tasks. By the end of this course, attendees will be confident in how they can import data, perform common manipulation tasks and visualise data. Along the way they will be introduced to a variety of data types including dates and categorical data. This course will be taught using the popular tidyverse set of packages and is ideal for those new to R who want to quickly get started with analytics in R.

This one day course is intended as a practical introduction to the basics of analytics. Taught using R, attendees will be introduced to ideas such as sampling, statistical testing and linear modelling. This course provides the foundations that are built upon for advanced analytic topics including machine learning.

Once you have started to use R for common manipulation tasks you will quickly find that you want to be able to do more. This one day course introduces the topics that you will need to be familiar with in order to get the most from R. This course will go into detail on the data types in R and how to interact with them at a lower level, how you can start writing functions and, as well as introducing some further tidyverse tools for iterating over data and manipulating specific elements.

This two day course is aimed at not only teaching an understanding of some of the most common machine learning techniques, but also the approach to implementing machine learning. During this course attendees will learn how to define a problem and prepare data, the range of techniques available for solving common problems and the approaches to take to evaluate models and achieve the best results possible.

As data scientists we can gain great insight from our analysis but to have impact we need to share the results of that analysis. For R users one of the simplest ways to do that is through shiny, a web development framework that allows us the power of interactive web applications combined with the power of R, all without leaving a language we are comfortable with. This one day introduction to shiny will help you to understand the building blocks of shiny and attendees will leave being able to create simple applications and dashboards.

As you start to write more re-usable code, your code will need to be more robust. In this one day programming course we introduce some of the functionality that allows your code to be more user friendly and stand up to unexpected use cases, as well as help you to get started with understanding how to resolve issues. By the end of this course attendees will be familiar with extended function writing topics, how to program in the tidyverse and the basics of object orientation in R as well as being introduced to tools for debugging and profiling.

As our data gets bigger, or simply shared across the business, we will typically find that it is stored in a database. To be able to get the most out of our analysis we need to be able to interact with the database from R, getting data into R for our analysis. This course will leave attendees with a basic understanding of relational databases as well as the ability to connect to a database, they will also learn basic SQL statements and tools in R for easily extracting data.

With an understanding of the basics, it is possible to build a variety of useful shiny applications. But to get the most from it we need to understand more about how it works and functionality that makes our apps more user friendly. In this one day course we will focus on teaching attendees how reactivity works in shiny, and the range of functionality available. Beyond this attendees will get a feel for some of the additional functionality available, from interacting with tables and plots to updating whole apps based on user input.

When it comes to forecasting time dependent data we need to consider a range of techniques beyond those common in machine learning to get the most from our data. In this one-day course attendees will be introduced to some of the common time series analysis techniques as well as how to implement and understand them in R. In addition we will cover some of the common manipulation tasks related to dates and times and how we can create visualisations to aid our analysis.

Many companies have a large amount of data stored as text that is not being used effectively. In this one-day course we will introduce how you can get started with analysing text data, from simple manipulation and sentiment analysis through to topic modelling. By the end of the course attendees will have a good understanding of the techniques as well as how to implement them in R.

Not only does R provide us with the tools for performing analysis but it also allows us to produce high quality documentation, meaning we can keep our reporting and analysis all in one place. This one day course introduces RMarkdown, a simple but effective way of creating documents directly from R. At the end of the course attendees will be able to generate reports in both HTML and Word or Powerpoint as well as create effective dashboards using flexdashboard.

This one day course is designed to introduce how R can be used for creating powerful visualisations of spatial data. From getting your spatial data into R and manipulating it into the correct format, to creating both static and interactive graphics. This course introduces the latest features of ggplot2 for working with simple features data, which represents spatial data in a tidy format, as well as the leaflet package in R for creating customisable, interactive graphics that can be incorporated into shiny applications.

For those already comfortable with programming in R, this one day course is designed to provide an introduction to more advanced topics that we can use to take our code one step further. Including introductions to additional object oriented systems and mode advanced function control, by the end of this course attendees will be able to make their code easier for end users to interact with, faster and more robust.

To take the final step to producing production ready shiny applications we need to think more about how we can create re-usable and testable code, in just the same way we would for any other R functions. In this course we will focus on how we can make our apps more robust to deployment by writing re-usable modules, how we can test, profile and debug our apps and how we can add final features that make our apps as user friendly as possible, from adaptive user interface to saving state of apps. By the end of this course attendees will be ready to deploy high quality apps into production environments.

Being able to build packages allows you to work more effectively and easily share code with colleagues or even the wider R community. In this course we will focus on how you can quickly get started with building packages, understand the benefits of package building best practices and be able to implement them. This includes being able to more efficiently write documentation, creating tests and understanding the benefits of version control systems and how they can enhance your package building.

If you don’t work for one of the big tech giant’s then deep learning may seem out of reach. Thankfully, recent developments have made the Keras Python package available to R users. This means we can now build our own deep networks, layer by layer, without the need to learn other tools. In this course we will introduce the concept of deep learning, how we can use it and where we can get the most from it, by the end of the day attendees will know how they can start to practically use deep learning on their own analysis problems.

As our data gets bigger we may need alternative ways to work with it. In this course we will introduce the sparklyr package for interfacing with Spark, allowing R users to get all of the benefits without having to leave R. By the end of this one day course attendees will be familiar with how they can connect to a Spark cluster and perform basic data tasks, how they can access Sparks machine learning capabilities and generate re-usable modelling pipelines.

Focused around a specific business problem, this one day workshop will work through the data analysis workflow to give attendees an understanding of how a data scientist would approach and look to answer an analytic question. The day will work through modelling approaches that are relevant to the question in hand, introduce best practices around modelling and data analysis and leave attendees with the ability to put into practice what they have seen.

Data Scientists and analysts are increasingly being asked to run or contribute to complex, multi-departmental projects with high expectations of success. Business and communication skills are rated as in top skills a data scientist needs to be successful. However, many individuals and teams struggle to develop them. The Trusted Consultant Programme helps data science and advanced analytics teams with a proven framework and tools they need to engage with stakeholders within their organisations in a positive, success-led manner.  By the end of the course attendees will have developed the essential skills required to work with business stakeholders, work as part of a team to manage the project, and present analytic results to non-technical audiences.