Bilbao, Spain

Big Data: Predicting the Future

when 1 July 2019 - 5 July 2019
language English
duration 1 week
credits 1 EC
fee EUR 500

Managing and processing large volumes of data, or “Big Data”, and gaining meaningful insights is a significant challenge facing the future of many companies. As a consequence, many business are demanding data analytics competencies for the job positions that are opening. This has a significant impact on a wide range of domains, including health care, marketing, human resources, digital economy, finance, etc.

Despite considerable progress in high performance, storage capacity, and computation power, challenges remain in identifying, clustering, classifying, and interpreting a large spectrum of information. That’s why it is necessary to acquire skills and knowledge in the fields of analytics, machine learning, and high-performance computing.
Thus, the goal of this workshop is to train professionals capable of completing cycles of data analysis (extraction, management, processing and visualization) to offer business analytics services to organizations, companies and individuals. Accordingly, participants will learn to master the main technologies of analysis and processing of large volumes of data, as well as other tools to enhance the value of the analyzed data and thus allow organizations to make more informed decisions.

Target group

People who want to acquire a solid base of data analysis and processing technologies to enable organizations to make more informed decisions. It is not necessary to have a computer science profile to participate in the workshop, although minimum analytical bases are desirable. We usually have a heterogeneous group in terms of academic profiles, a diversity that creates an enriching environment for learning full of experiences, problems and shared solutions.

Course aim

At the end, the participant must be able to understand and use analytical methods that allow any organization to find opportunities for greater margins and profitability through analytical techniques.
More specifically, it is intended that students can:

Understand the difference between unsupervised and supervised machine learning methods to improve the future decisions of any given company.
Learn what can I contribute to my business and where can it can be applied to improve both financial and operational efficiency
Understand the different techniques of Machine Learning to find business opportunities in companies.
Develop several application cases so that through benchmarking, the participants can then find opportunities in the future.

Credits info

1 EC
Through an active learning hands-on approach, we will carry out a different set of activities to understand and solve different organizational problems’ using supervised and non-supervised machine learning methods.

Fee info

EUR 500: Total fee: 500 €
Discounts: from 325€