Blog - 22 Jul 2022
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Data Science & Analytics
Data Engineering
EARL
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The range of workshops available at EARL 2022 is designed to help data practitioners extend their skills via a series of practical challenges. Led by specialists in Shiny, Purrr, Plumber, ML and time series visualisation, you’ll leave with tips and skills you can immediately apply to your commercial scenarios.

data science, data skills, upskill, workshops, EARL, EARL conference,

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2022-07-21T23:00:00Z

Time to upskill in R? EARL’s workshop lineup has something for every data practitioner.

With data skills in such high demand, workshops events such as EARL provide the perfect blend of tuition and knowledge exchange to enhance existing skill sets and expand horizons.

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Data Science & Analytics

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It’s well-documented that data skills are in high demand, making the industry even more competitive for employers looking for experienced data analysts, data scientists and data engineers - the fastest-growing job roles in the UK. In support of this demand, it’s great to see the government taking action to address the data skills gap as detailed in their newly launched Digital Strategy.

The range of workshops available at EARL 2022 is designed to help data practitioners extend their skills via a series of practical challenges. Led by specialists in Shiny, Purrr, Plumber, ML and time series visualisation, you’ll leave with tips and skills you can immediately apply to your commercial scenarios.

The EARL workshop lineup.

Time Series Visualisation in R.

How does time affect our perception of data? Is the timescale important? Is the direction of time relevant? Sometimes cumulative effects are not visible with traditional statistical methods, because smaller increments stay under the radar. When a time component is present, it’s likely that the current state of our problem depends on the previous states. With time series visualisations we can capture changes that may otherwise go undetected. Find out more.

Explainable Machine Learning.

Explaining how your ML products make decisions empowers people on the receiving end to question and appeal these decisions. Explainable AI is one of the many tools you need to ensure you’re using ML responsibly. AI and, more broadly, data can be a dangerous accelerator of discrimination and biases: skin diseases were found to be less effectively diagnosed on black skin by AI-powered software, and search engines advertised lower-paid jobs to women. Staying away from it might sound like a safer choice, but this would mean missing out on the huge potential it offers. Find out more.

Introduction to Plumber APIs.

90% of ML models don’t make it into production. With API building skills in your DS toolbox, you should be able to beat this statistic in your own projects. As the field of data science matures, much emphasis is placed on moving beyond scripts and notebooks and into software development and deployment. Plumber is an excellent tool to make the results from your R scripts available on the web. Find out more.

Functional Programming with Purrr.

Iteration is a very common task in Data Science. A loop in R programming is of course one option – but purrr (a package from the tidyverse) allows you to tackle iteration in a functional way, leading to cleaner and more readable code. Find out more.

How to Make a Game with Shiny.

Shiny is only meant to be used to develop dashboards, right? Or is it possible to develop more complex applications with Shiny? What would be the main limitations? Could R and Shiny be used as a general-purpose framework to develop web applications? Find out more.

Sound interesting? Check out the full details – our workshops spaces traditionally go fast so get yourself and your team booked in while there are still seats available. Book your Workshop Day Pass tickets now.

Amanda Cleverly

Content Lead

Ascent

Amanda leads Ascent’s content strategy as part of her senior marketing role. With a strong background in data science and a passion for technology and innovation, her flair for compelling communications enables her to explore human, technical and business subject matter across diverse industries.

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