Data Science Technical Training
Pinpoint the path to data-science excellence
We assess teams and individuals and prioritise training to build internal capability, guided by Data Science Radar – a tool
representing the cumulation of our experience in data science consulting and participation in the R community. Data
Science Radar leverages a proprietary ‘trait’ model of data science skills to help organisations recruit and retain the right
talent – and enable individuals to prioritise their learning and development.
The DSR traits are: Programmer, Modeller, Visualiser, Communicator, Data Wrangler and Technologist
Contact us to discuss an initial no cost review of your teams capabilities using this assessment tool.
> Introduction to R for Analytics | 2 days | Programmer
Explores common data tasks, including how to import data, perform common manipulation tasks and visualise data. Introduces a variety of data types including dates and categorical data.
> Fundamentals of Modelling in R | 1 day | Programmer/Modeller
The basics of analytics, including sampling, statistical testing and linear modelling. Provides the foundations for advanced analytic topics including machine learning.
> Programming in R for Analysts | 1 day | Programmer
Explains data types in R and how to interact with them at a lower level, such as how to start writing functions. Introduces further tidyverse tools for iterating over data and manipulating specific elements.
> Introduction to Shiny | 1 day | Visualiser/Programmer
Shiny is a web development framework that combines interactive web applications with R. This course helps attendees to understand the building blocks of shiny and create simple applications and dashboards.
> Reporting Tools in R | 1 day | Communicator
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.
> Machine Learning in R | 2 days | Modeller
Teaches some of the most common machine learning techniques and their implementation in R. Covers defining a problem, preparing data, the range of techniques available for solving common problems and how to evaluate models and achieve the best results possible.
> Intermediate R Programming | 1 day | Programmer
How to make code more user friendly, stand up to unexpected use cases, and resolve issues. Explains extended function writing topics, how to program in the tidyverse and the basics of object orientation in R as well as introducing tools for debugging and profiling.
> Databases and SQL from R | 1 day | Data Wrangler
This course leaves 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.
> Intermediate Shiny | 1 day | Visualiser/Programmer
How reactivity works in shiny, and the range of functionality available. 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.
> Time Series Analysis in R | 1 day | Data Wrangler/Visualisers/Modeller
Introduces some of the common time series analysis techniques as well as how to implement and understand them in R. Also covers some of the common manipulation tasks related to dates and times and how to create visualisations to aid analysis
> Web Scraping and Text Analysis in R | 1 day | Data Wrangler/Visualiser
How to 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
> Data Visualisation in R | Data Wrangler/Visualiser
Discover and understand the principles required to create powerful visualisations which effectively and accurately communicate the stories inside data. Using the powerful an expressive ggplot2 package you will learn how to apply these principles and also the common pitfalls to avoid when creating your own visualisations.
> Package Building | 1 day | Technologist/Programmer
How to get started with building packages. Including being able to write documentation more efficiently, create tests and understand the benefits of version control systems and how they can enhance your package building
> Advanced R Programming | 1 day | Programmer
Introduces additional object oriented systems and more advanced function control. By the end of this course attendees will be able to make their code faster, more robust, and easier for end users to interact with.
> Advanced Shiny | 1 day | Visualiser/Programmer
How to make apps more robust by writing reusable modules. How to test, profile and debug apps and how to
add final features that make apps as user friendly as possible, from adaptive user interface to saving state of apps.
> Deep Learning with Keras for R | 1 day | Modeller
Introduces 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.
> Spark and R with sparklyr | 1 day | Data Wrangler
Introduces the sparklyr package for interfacing with Spark, allowing R users to get all of the benefits without having to leave R. Includes how to connect to a Spark cluster and perform basic data tasks, and how to access Sparks machine learning capabilities and generate re-usable modelling pipelines.
> Data Science in Practice | 1 day | Communicator
Explains how a data scientist would seek to answer a specific business question using analytics – working through relevant modelling approaches, modelling best practices and data analysis and leaving attendees with the ability to put into practice what they have seen.
Delegates on all courses will receive –
- Full days of interactive training from one of our dedicated Mango Data Scientists ( we can break courses into half days at client request)
- Comprehensive electronic course materials
- Interactive exercises
- Attendance certificates
- 3 months post course support
Our mission is to promote the adoption of advanced data science techniques such as AI to organisations in the Sheffield City Region and help them find additional value, efficiencies and insights in their data. We can do this on a consultancy basis but are also able to provide training to organisations across the leadership, commercial and technical fields. As well as the 'Art of the Possible' series featured in detail here, we can also provide Beginner / Intermediate and Expert Training Courses in the technical aspects of data science programming in both R and Python languages.View Website