For those who have a basic understanding of programming, to ensure that their data science projects always follow best practices in all, and to help emphasise the importance of best practices when working in a team – as we know, Data Science is a team sport. While all the Mango training courses help to instil these best practices; this course focuses on what the options are and why we need to use them in a language agnostic setting. This course outlines the key best practices associated with the 6 core traits of a data science team and project: communication, data wrangling, modelling, programming, technology, and visualisation.
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.
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.
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.
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.
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.
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.
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 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.
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.