Machine Learning School in Seville

March 26-27, 2020, Seville, Spain

Machine Learning is transforming many industries while enabling new types of products and services nobody even dreamed of until recently. However, the skill set required to develop real-life Machine Learning applications have mostly remained the playground of the few privileged academics and scientists. The world and the global workforce cannot afford to stay behind the curve on this key technology enabler, so we urgently need to produce a much larger group of ML-literate professionals such as developers, analysts, managers, and subject matter experts.

To meaningfully contribute on this matter, BigML is bringing the second edition of our Machine Learning School to Seville. We will hold a two-day crash course ideal for business leaders, industry practitioners, advanced undergraduates, as well as graduate students, seeking a quick, practical, and hands-on introduction to Machine Learning to solve real-world problems. This Machine Learning School will serve as a good introduction to the kind of work that students can expect if they enroll in advanced Machine Learning masters.

Comment about the Machine Learning School using #MLSEV


Guillem Vidal

Machine Learning Engineer at BigML

jao, Ph.D.

Co-Founder and Chief Technology Officer at BigML

Mercè Martín Prats, Ph.D.

VP of Insights and Applications at BigML

Poul Petersen, M.Sc.

Chief Infrastructure Officer at BigML


Juan Ignacio de Arcos

VP Business Development at BigML


Tom Dietterich, Ph.D.

Co-Founder and Chief Scientist at BigML, Director of Intelligent Systems Research at Oregon State University

Andrés González

CTO & Cofounder at

Cristina Rodríguez

Projects Manager at Talento Transformación Digital

Delio Tolivia

Technical Manager of R&D&I Projects at Talento Transformación Digital

Ed Fernández

Board Director at Arowana

Enrique Dans, Ph.D.

Senior Advisor for Innovation and Digital Transformation at IE University

Jan W. Veldsink

Lead Artificial Intelligence and Machine Learning Compliance Domain at Rabobank

José Cárdenas Lafuente

Manager Technical Services at Indorama

Kevin Nagel

Consultant / Data Scientist at Inform

Michael Skiba, Ph.D.

International Economic Crime Expert at Dr. Faud

Roy Prayikulam

Head of Professional Services at Inform

Schedule of Lectures

The goal of this Machine Learning School is to introduce basic as well as more advanced Machine Learning concepts and techniques that will help you boost your productivity significantly. All lectures will take place at EOI Andalucía from 8:30 AM to 7:00 PM CET during March 26 and 27, 2020.

Day 1

08:30 AM - 09:00 AM
Registration, Breakfast, and Networking
09:00 AM - 09:30 AM
Opening Remarks
by Juan Espadas (City Major), Rogelio Velasco y Manuel Ortigosa (Regional Government), and a Representative of the Spanish Government
09:30 AM - 10:15 AM
ML platformization and AutoML in the Enterprise
10:15 AM - 11:00 AM
What is Machine Learning: A Business Perspective
11:00 AM - 11:30 AM
Coffee Break and Networking
11:30 AM - 12:15 PM
State of the Art in ML
by Tom Dietterich (BigML)
12:15 PM - 01:15 PM
Supervised vs Unsupervised Learning techniques
by Poul Petersen (BigML)
01:15 PM - 02:00 PM
Linear Regression and Evaluations
by Poul Petersen (BigML)
02:00 PM - 03:00 PM
Lunch and Networking
03:00 PM - 03:45 PM
Fraud in a Digital Environment or "PsychTech"
03:45 PM - 04:15 PM
Benetifs of using ML to monitor your Low Risk Customers
04:15 PM - 05:00 PM
An hybrid AI approach to tackling fraud
05:00 PM - 05:30 PM
Coffee Break and Networking
05:30 PM - 06:30 PM
My first BigML Project

Day 2

09:00 AM - 09:45 AM
Reducing dimensionality with PCA
by Poul Petersen (BigML)
09:45 AM - 10:30 AM
Predictions techniques in ML
by Mercè Martín (BigML)
10:30 AM - 11:00 AM
Searching for anomalies
by Tom Dietterich (BigML)
11:00 AM - 11:30 AM
Coffee Break and Networking
11:30 AM - 12:15 PM
Practical anomaly detection examples with BigML
by Guillem Vidal (BigML)
12:15 PM - 01:00 PM
by Poul Petersen (BigML)
01:00 PM - 01:30 PM
Applying Classification and Regression to Quality Optimization
01:30 PM - 02:00 PM
Optimization of passengers waiting time in elevators using ML
02:00 PM - 03:00 PM
Lunch and Networking
03:00 PM - 03:30 PM
Applying Topic Modelling to improve Operations
03:30 PM - 04:30 PM
04:30 PM - 05:00 PM
Coffee Break and Networking
05:00 PM - 06:00 PM
From my first BigML Project to Production
06:00 PM - 06:30 PM
Closing Remarks
by Francisco Velasco (EOI), Francisco Fernández Lineros (City Council), and Juan Ignacio de Arcos (EOI & BigML)
06:30 PM - 07:00 PM
Cofee and drinks
BUY TICKETS Price: 70€ + VAT (21%)


EOI Andalucía Leonardo da Vinci Street, 12. 41092. Cartuja Island, Seville, Spain

How to arrive

Seville-Santa Justa
city transport (24 min) - taxi (20 min) The main railway station in Seville
Seville Airport
city transport (82 min) - taxi (20 min)
Prado de San Sebastian
city transport (36 min) - taxi (17 min) Bus station in the center of Seville

Right in front of both stations and the airport there are taxi stops with plenty of taxis available all day.

Recommended Hotels When you book your room, please make sure you mention you are coming to BigML's Machine Learning School.

Ribera De Triana Hotel

5% discount on the prices available on the hotel page. To apply the discount you need to book your room through their website and use the discount code: BIGML.

Exe Isla Cartuja Hotel

Single and double rooms, rate range: 85€ - 89€ (breakfast and 10% VAT included). Book your room through their website.

NH Plaza de Armas Hotel

Single and double rooms, rate range: 126€ - 138€ (breakfast and 10% VAT included). To apply this offer you need to email to: or call to +34 954901992 and use the reference number: MB2206747.

Sevilla Renacimiento Barceló Hotel

Single and double rooms, rate range: 138€ - 154€ (breakfast and 10% VAT included). To apply this offer you need to email to: and use the reference: BIGML. Offer valid until February 15th, 2020 and it is subject to availability.

Organized by:


In collaboration with:

EOI - Escuela de Organizacion Industrial
Junta de Andalucia
Ayuntamiento de Sevilla