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Postgraduate Program Enterprise Data Science & Analytics

EDSA

Postgraduate Program in Enterprise Data Science & Analytics

Developed in partnership with Microsoft, the Postgraduate Program in Enterprise Data Science & Analytics will present the methodologies and tools that will transform data into information, on which enterprises can base strategic information on entering new markets, launching new product or service lines, optimizing processes, transforming business models and, generally, competing in a market increasingly driven by data-driven decisions. This program aims to qualify professionals in data science and advanced analytics, as well as in the creation of predictive models and their practical application in enterprise environments.

The applications for this program are open between September 24th and October 31st, 2024. To apply, click here.

  • Vagas

    Format

    After Working Hours

  • Media

    Length and ECTS

    2 semesters
    (60 ECTS)

  • Semestres

    Attendance

    2 to 3 times
    a week

  • Lingua

    Start Date

    February 2024

Partner Entity

  • Microsoft
    Microsoft
Who is it for? image

Who is it for?

This program is aimed at professionals interested in deepening their knowledge in data science and advanced analytics, as well as in the creation of predictive models and their practical application in enterprise environments. It aims to tackle the shortage of highly qualified professionals in this field, with one of the highest growths in the current market of information systems.

EDUNIVERSAL

Ranked among the best in the best program in Big Data Management in Portugal and the 3rd best in the World by Eduniversal, an international agency that publishes the annual ranking of the best MBA and Master programs in the world.

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Goals

The main goal of this program is to train technical staff to use Big Data and Machine Learning tools and methodologies in the:

  • Exploration and transformation of data;

  • Creation of data models and data visualization;

  • Application of statistical methods to data;

  • Application of data science methodologies;

  • Implementation and validation of Machine Learning models;

  • Application of data science techniques to common scenarios in enterprise environments.

NOVA IMS

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