London Data Science Summit

Learn from industry experts and attend inspiring keynotes, practical data science workshops and numerous networking opportunities



Explore Data Science in Practice

20-22 October 2017
The Royal Statistical Society, 2 Errol St, London EC1Y 8LX

Brought to you by

organisers

For analysts, researchers and developers

Join us to network, develop new skills and gain insight into the evolving field of data science.

Talks

Friday 20 October

Talks and Networking

Workshops

Saturday 21 October

Hands-on Workshops

Venue

Sunday 22 October

Hands-on Workshops


DEEP DIVE WORKSHOPS

Our series of workshops will cover:

  • Machine Learning
  • Neural Networks and Deep Learning
  • Big Data Technologies
  • Text Analytics and Natural Language Processing

Find out more! Download our summit brochure for further information about our speakers and series of hands-on data science workshops.

Receive our PDF Summit brochure and schedule

Why attend

Engage with industry experts

Gain new knowledge and insights from a range of sectors, from research and bioinformatics to business and finance

Upskill in Data Science

Learn how to implement state-of-the-art techniques to leverage the latest tools for Machine Learning, Deep Learning and Big Data Analysis.

Network with others in their field

Network and connect with researchers, data scientists and technologists from different domains and industries

Get exposed to different languages and libraries

Register Now

Interested?

Head to our registration tab to book your place. If you have any questions send an email to events@cambridgespark.com or fill in our contact form. We’ll be sure to get back to you soon.

20 October - Main Conference

09:00 Conference Registration
09:15 Welcome to the London Data Science Summit
09:30 Opening Keynote: Data Centric Engineering (Prof. Mark Girolami, Alan Turing Institute)
10:00 (Responsible) Subjective Machine Vision (Dr. Miriam Redi, Wikimedia Foundation)
10:30 Building and Deploying a Real-time Banking Fraud Detection System (Dr. Karthik Tadinada, Featurespace)
11:00 Tea / Coffee Break
11:30 Demand forecasting and capacity planning for government services (Francine Bennett, Mastodon C)
12:00 Generation Genome? Opportunities and challenges for a future awash with genetic data (Patrick Short, Heterogeneous)
12:30 Deploying Machine Learning models in real business (Marcin Druzkowski, Ocado Technology)
13:00 Lunch / Networking
14:00 Demystifying Deep Learning (Petar Veličković, University of Cambridge)
14:45 Computational Privacy (Dr. Yves-Alexandre de Montjoye, Imperial College London)
15:15 Tea / Coffee Break
15:45 Artificial Intelligence in the Enterprise (Dr. Martin Goodson, Evolution AI)
16:15 Machine Learning for Finance (Matthew O'Kane, Accenture Analytics)
16:45 Closing Keynote: Artificial Intelligence and the Two Singularities (Calum Chace)
17:15 Networking Drinks

Further information

Workshops

Workshops will assume some basic knowledge about programming in Python.

Not ready yet?

Explore what’s to come by downloading our tutorial pack covering a range of core techniques in data science. You’ll receive an update as we announce our speaker lineup.

Receive a free Data Science e-book to get started

Interested?

Head to our registration tab to book your place. If you have any questions send an email to events@cambridgespark.com or fill in our contact form. We’ll be sure to get back to you soon.

21 October - Hands-on Workshops

09:00 Session 1
09:30 Analyzing and Manipulating Data with Pandas
09:45
10:00
10:45
11:00 Tea / Coffee Break
11:30 Principle Component Analysis
12:00
12:30
13:00 Lunch / Networking
13:40 Supervised Machine Learning using Scikit-learn (Part I)
14:15
14:45
15:15 Tea / Coffee Break
15:45 Supervised Machine Learning using Scikit-learn (Part II)
16:15
16:45
17:00 Conference close

22 October - Hands-on Workshops

09:00 Session 1
09:30 Neural Networks and Deep Learning using Keras (Part I)
09:45
10:00
10:45
11:00 Tea / Coffee Break
11:30 Neural Networks and Deep Learning using Keras (Part II)
12:00
12:30
13:00 Lunch / Networking
13:40 Introduction to Natural Language Processing (Part I)
14:15
14:45
15:15 Tea / Coffee Break
15:45 Introduction to Natural Language Processing (Part II)
16:15
16:45
17:00 Conference close

Further information

Workshops

Workshops will assume some basic knowledge about programming in Python.

Not ready yet?

Explore what’s to come by downloading our tutorial pack covering a range of core techniques in data science. You’ll receive an update as we announce our speaker lineup.

Receive a free Data Science e-book to get started

Interested?

Head to our registration tab to book your place. If you have any questions send an email to events@cambridgespark.com or fill in our contact form. We’ll be sure to get back to you soon.

Prof. Mark Girolami

Fellow
Alan Turing Institute

Session: Data Centric Engineering

Dr. Yves-Alexandre de Montjoye

Lecturer in Computational Privacy
Imperial College London Data Science Institute

Session: Computational Privacy

Dr. Karthik Tadinada

Director of Data Science
Featurespace

Session: Building and Deploying a Real-time Banking Fraud Detection System

Calum Chace

Book Author

Session: Artificial Intelligence and the Two Singularities

Dr. Martin Goodson

Chief Scientist
Evolution AI

Session: Artificial Intelligence in the Enterprise

Matthew O'Kane

Managing Director
Accenture Analytics

Session: Machine Learning for Finance

Petar Veličković

PhD
University of Cambridge

Session: Demystifying Deep Learning

Dr. Miriam Redi

Research Scientist
Wikimedia Foundation

Session: (Responsible) Subjective Machine Vision

Patrick Short

CEO and co-founder
Heterogeneous

Session: Generation Genome? Opportunities and challenges for a future awash with genetic data

Francine Bennett

CEO and co-founder
Mastodon C

Session: Demand forecasting and capacity planning for government services

Marcin Druzkowski

Machine Learning Engineer
Ocado Technology

Session: Deploying Machine Learning models in real business

Check out our past Data Science Summit and videos.