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Fernando Velasco



Artificial Intelligence on Data Centric Platform

Morning | 09:00 - 13:30


Digital Transformation starts with data. What if a solution existed that put data at the center, in a single place, serving all applications around it? This training will include a demonstration in a distributed data-centric platform which provides a data intelligence layer, composed of artificial intelligence models able to make use of a whole company’s data.

Nowadays, one of the most innovative techniques in the realm of artificial intelligence is Deep Neural Nets. Among the many applications, language modelling, machine translation and image generation are receiving particular attention. Deep nets are also powerful in predictive modelling ambits such as stock pricing and the energy industry. We will address a few case studies modeled with TensorFlow, running on Stratio’s data-centric product in a distributed cluster.


– Internet Connection
– Machine Learning knowledge (we will address some Deep Learning concepts, but no background is required)
– Basic Python (some knowledge of TensorFlow and Keras would be useful, but not mandatory)

Nature of the training:

By taking a data-centric approach and building their IT systems around the concept of a data-centric architecture, companies such as Netflix and Google, have gained a very real and seemingly unreachable status as digital disruptors. With the company’s data in a single, central point, all its applications can access it in the same place - no more inconsistencies or data duplication across applications as these no longer own data, but access it from a single place. The informational and operational silos of the company are merged. And, because you cannot cover all informational and operational use cases of a company with a unique datastore, the best NoSQL technologies and MPP are combined, according to the type of use and data.

In this context, advanced machine learning algorithms are run in the data-centric platform and therefore, can be trained using the whole company’s data. The resulting models can be exploited via microservices, providing maximum data intelligence in real-time to all the applications of a company. This decentralized microservices-based approach enforces scalability with respect to the number of applications and users that need to access both the data and the intelligent models built upon them.

In this tutorial, we will use the data intelligence layer of Stratio DataCentric to showcase the aforementioned real use cases which rely upon artificial intelligence methods, for both supervised and unsupervised learning. We will make use of Deep Learning for that purpose, addressing sequential data (via Recurrent Neural Nets) and unlabeled images (relying on generative models).


Big Data Spain will issue the certificate for this course.


Developers, Data Scientists. Mainly technical profiles, with interests in Deep Learning and Artificial Intelligence.

Bio of the instructor:

Fernando Velasco Lozano is Data Scientist at Stratio. He is enthusiastic about mathematical modeling, data and innovation. His experience includes academic research in the Algebraic Geometry area, and his passion is Data Science. His area of expertise includes Deep Learning and Behavioral Algorithms.