Part-Time Bootcamp

Data Science

Futureproof your skillset with Machine Learning, R, Data Visualisation and PowerBI
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This 18-week bootcamp teaches you the skills you need to deliver data science projects effectively. You learn the core skills and concepts in data science whilst advancing to topics like deep learning and natural language processing to enable you to meet modern business needs. Every week, you’ll do two evening sessions that blend lecture and labs to ensure you get practical experience that will help you become a successful data scientist.

This unique accelerated Bootcamp covers the fundamentals that everyone will need in order to be successful in data science – data mining, data visualisation, data exploration, machine learning, AI and work practices. You will work on real datasets applying the latest techniques for arriving at conclusions and making predictions.


The demand for data science skills has never been higher. Increasingly software engineers, web developers and product managers are embedding analytics and data mining capabilities within their deployments.

This Bootcamp is ideal for people looking to acquire data science skills needed to stay ahead of the game – typically IT or finance professionals – risk, accountants, analysts – as well as business & data analysts, researchers, academics and software engineers seeking to learn more, upskill and gain a competitive advantage from their data.

Comfortable with a robust data science process and able to implement the process in your own projects
Able to analyse data using popular platforms (R, Power BI) and produce quality reports and conclusions
Benefit from practical industry-led workshops that cover the most popular technologies and platforms (R, Power BI) for data science and their application.
Well-versed in multiple models / algorithms that can be applied to make predictions and able to identify and apply the right ones for different data science challenges
Knowledgeable about techniques for working with and making predictions based on non-tabular data
Understand deep learning and natural language processing topics and their application
Apply learning to your own dataset and other pre-defined dataset challenges
Aware of further resources for continued self-learning
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01/04/2020 - 30/08/2020

18 weeks

Every Thursday & Friday evening (18:15 - 21:15)

Regular Rate

Early Bird Rate (15% off)

Claremont Avenue, Glasnevin Dublin 11

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Key learning areas

Data Exploration

By exploring your data you will uncover hidden trends and insights. Our faculty are skilled practitioners in R - the most prolific programming language for data science applications - and they will upskill you in bespoke packages for outlier detection, duplicate removal, generating frequency tables and more. Getting to know your data doesn't require in-depth programming skills, R is straightforward and we will teach you the basics before the course starts, so you can hit the ground running and build impeccable models by the end.

Machine Learning

Increasingly, ML is being employed by engineers in chatbots, automated vehicles, image detection, personal assistants and a plethora of finance and marketing avenues. Software engineers and data analysts are bringing machine learning and artificial intelligence solutions to bear, automating the analysis process. Our course will teach you the core statistical principles and algorithms for ML up to and including the basics of constructing convolutional neural networks (CNNs).

Data Visualisation

There is an increasing need to extract value from data investments. Data Visualisation enables you to present your new knowledge clearly and persuasively. Participants learn about new tools and techniques that deliver state-of-the-art data visualisations quickly and easily. You learn from best practice and develop a workflow that takes you from raw data to impressive visuals using the latest tools including Charticulator and Data Illustrator.

Data Engineering and Machine Learning Operations

Learn how to build and deliver end-to-end data and machine learning pipelines that take dirty or distributed data, consolidate it, build relevant features, train and retrain models, and publish for use in applications. The exploratory data analysis and machine learning workflows built throughout the course will be turned into scalable solutions that can fit into a production software environment. In practice, this means you will be able to lead and manage your own Data Science projects.

Action Project

You will also have the opportunity to apply your skills and knowledge, with organisations including Dolmen Design, Epic Museum and Met Eireann on the Action Project. This is where you, your team and the project partner build actionable solutions to data problems over 6 weeks, gathering insights and visualising the results to provide tangible business value.

Meet the faculty teaching this Bootcamp

Steph Locke

Steph is one of only fifty-eight individuals in the world to be recognised with Microsoft’s Artificial Intelligence Most Valued Professional award. She is the founder of Locke Data, a UK-based data science consultancy.

Dr. Finn Macleod

Dr. Finn Macleod is a former mathematician with a PhD in predictive complexity. He has built, sold and designed dashboards for clients such as Thomson-Reuters, Formula 1 (via Meshh) and Heineken.

Mick Cooney

Mick is a quantitative analyst working on data science type projects in financial services. He advises and assists financial services companies in managing and implementing data-driven processes within their organisations.

Dr. Francesca Bonin

Francesca Bonin is a Research Scientist at IBM Research Ireland, working on AI and Natural Language Processing (NLP). In IBM Research AI, she has been part of the Project Debater team, developing breakthrough AI technologies for the last IBM AI Gran Challenge

Friedrich Wetterling

Friedrich has authored and co-authored twenty international peer-reviewed journal publications, and is an advocate for non-invasive imaging technology with a main focus on Magnetic Resonance Imaging (MRI). In 2016, he joined FIRE1 - a medical device company in Dublin as senior radio-frequency engineer.

Jonathan Symmonds

Jonathan is Co-Founder of Sophoria Visual Effects studio. With over 18 years experience in the film and games industry he has worked on Avatar, Where the Wild Things Are, Prince of Persia and more. More recently, Jonathan led the animation departments for “The Game of Thrones” series at Pixomondo and was nominated three times for a VES Award.

Aoife D'Arcy

Aoife is the Managing Director of data consultancy The Analytics Store. Her expertise ranges from telling stories with data visualisations, to machine learning, to developing analytics strategy, and just about everything else in between.

Fintan Buckley

Fintan is the CEO and Co-Founder of Ubotica Technologies, a Computer Vision and AI start-up based in DCU Alpha, and with a design centre in Spain. Ubotica is developing enabling technologies and solutions for decision making "on the edge", targeting Earth Observation and Industry 4.0 applications.

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