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9:00 AM - 5:00 PM

Data Science Festival Workshop Day

9:00 am-
5:00 pm
April 20th , 2018, Friday

Join us for a day of deep dive learning at our 3.5-hour workshops, offering you a chance to take part in a combination of amazing and enlightening workshops with experts in their field. Lunch will be provided from 12:30PM-1: 30 PM giving you a chance to network and mingle with your fellow attendees.

Please read the workshop speaker information and bio below for prerequisites and what to bring to your workshop. You have the option of a Half Day or Full Day ticket, you will not be able to change workshops during the day.

All workshops tickets also give you a ticket to the Saturday MainStage Day on April 21st also at Skillsmatter. You will be sent your workshop ticket immediately, your ticket to the Mainstage event will be sent 1 week before the event takes place. Tickets are non-transferable and non-refundable.

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Introduction to Apache Spark in Python for Big Data Processing –Raoul-Gabriel Urma

Intro to Python – Robert Mastrodomenico

Introduction to Shiny – Tatiana Kim

Distributed processing of graph data with Neo4j and Apache Spark. – Iryna Feuerstein



Getting to grips with the tidyverse (R) – Colin Gillespie

Bank to the Future: Bitcoin meets Apache Hadoop – Daniel Cook

Building a Python data-driven product… in 3.5 hours – Gianluca Campanella

Telling stories with Data – Sophie Sparkes

Colin Gillespie
Jumping Rivers Ltd
Workshop Abstract: The tidyverse is essential for any statistician or data scientist who deals with data on a day-to-day basis. By focusing on small key tasks, the tidyverse suite of packages removes the pain of data manipulation. In this tutorial, we'll cover some of the core features of the tidyverse,…
Daniel Cook
Bitcat Software
Workshop Abstract: We’ve long assumed that in order to move money from one account to another reliably that we need to employ transactions to wrap the debit from one account and the credit to another.  The blockchain has challenged this thinking, recording all transactions on a ledger in an append only…
Gianluca Campanella
Talk Abstract: Lessons learned from teaching Data Science. The current shortage of talent in Data Science has led to the creation of a plethora of courses and workshops, both online and in-person — but are we reaching the right audience, and giving them the right skills to close the talent gap? Starting…
Iryna Feauerstein
Workshop Abstract: Distributed processing of graph data with Neo4j and Apache Spark.In this hands-on session first the main concepts behind graph models and querying of graph data will be introduced by means of both Neo4j's graph querying language Cypher and Apache Spark's API for graphs GraphX. Attendees will learn the…
Raoul-Gabriel Urma
Cambridge Spark
Workshop Abstract: This workshop will provide a hands-on introduction to the Big Data ecosystem, Hadoop and Apache Spark in practice. Through practical activities in Python, you will learn how to apply Apache Spark on a range of datasets to process and analyse data at scale. After taking this workshop you…
Robert Mastrodomenico
Global Sports Statistics
Workshop Abstract: Python is awesome, I may be biased but it can do loads of things and Data Science is one of them. With Data Science being such a wide subject we will concentrate on dealing with and manipulating data in Python. We begin by doing a whistle-stop tour of the…
Sophie Sparkes
Workshop Abstract: Humans are visual creatures. Visualising data makes it easier for us to explore it, find insights, and helps people understand those insights to make decisions. In this hands-on workshop learn how to to visually analyse your data to find insights, then quickly turn those insights engaging and compelling,…
Tatiana Kim
Mango Solutions
Workshop abstract: One of the key skills for a data scientist is communication of information and in R that generally means shiny. Shiny is an R package that allows users to quickly build web interfaces to analysis without having to leave R. In this workshop we will introduce the basics…