Term 0: Pre-Program

Refresher on basic statistics and linear algebra.

Allow to develop intermediate level skills in Excel.

Develop the anility to code and to become fluent in the use of different ananlytics tools (R, Python, SAS, Rapid Miner,…).

In cooperation with

TERM 1: Foundations

This course will be given to clarify the usefulness and the importance of the statistical approaches and how statistics can considerably help the decision making process. To this direction a brief introduction to basic principles of probability theory will be given and their connection to problems in statistics. Basic statistical ideas for descriptive statistics and data visualization will be discussed together with problems of statistical inference like estimation and hypothesis testing. Regression type models will be discussed, including simple, multiple, logistic regression and a brief introduction to generalized linear models. The Bayesian approach in statistical modeling offering certain possibilities with huge datasets will be introduced and worked. Finally time series and forecasting will be introduced.
Despite everyone’s good intentions, hard work and strong ideas, too many projects end up creating unneeded, unusable, and unsellable products. Agile and design thinking offer a different and effective approach to product development, one that results in valuable solutions to meaningful problems. In this course, you’ll learn how to determine what’s valuable to a user early in the process by focusing your team on testable narratives about the user and creating a strong shared perspective.
Programming Methodology teaches programming language along with good software engineering principles. Emphasis is on good programming style and the built-in facilities of this programming language.

This course guides students through fundamental project management concepts and behavioral skills needed to successfully launch, lead, and realize benefits from projects in organizations. In this course, students explore project management with a practical, hands-on approach through case studies and class exercises.

The course will provide students with fundamental knowledge about leading in the digital age. Based on management concepts, scientific insights and practical examples, the course will explain why and how leadership will change. In addition, the students will learn to use adequate leadership tools. The course is looking at three leadership levels: leading a company, leading a team and leading individual employees.

This course helps students to develop their consulting and advisor skills and practices.

TERM 2: Economics of Digital Transformation

The course delves into the core concepts of digital transformation in organizations and digital business model development. It furthermore sheds light onto key digital technologies and architectures driving and shaping digital transformation and business model development.

This course will delve into the multiple facets of leading and magaging digital transformation programs and projects.

The main objective of the course is to introduce the concept of Digital Innovation and Transformation to transform business processes, enhance customer experience, or create new business models. The course will examine how and when digital technologies can be used to innovate and gain competitive advantage. At the end of the course, students should be able to foresee such areas in which technology can be used to transform business processes, products, services, or business models and create a sustainable competitive advantage.

This course provides and overview of the disciplines of governing data, covers the essential components of an enterprise-wide program, and outlines a roadmap to execute a successful data governance program. In addition the course makes data governance real and tangible by illustrating the concepts, principles, and practices using a case study of Data Governance in different contexts and industries. Last but not least, it presents a philosophical, social, and legal inquiry into the impact of digital communications upon privacy & its meanings, in order to prepare students to recognize, contextualize, and analyze privacy challenges created by new information technologies.

TERM 3: Technologies & Analytics

This course gives a basic introduction to machine learning (ML) and artificial intelligence – AI. With an algorithmic approach, the students are given a practical understanding of the methods being taught, as well as through making their own implementation of several of the methods.

This course offers lecture, laboratory, and online interaction to provide a foundation in data management concepts and database systems. It includes representing information with the relational database model, manipulating data with an interactive query language (SQL) and database programming, database development including internet applications, and database security, integrity and Datawarehouse technologies.

This course alows students to develop in-depth knowledge of the emerging collection of tools and technologies used in Big Data in order to have the ability to deal with large-scale structured and unstructured collections of data, moving them into a Hadoop cluster from different sources and making up MapReduce applications. It will cover also new technologies such as IOT and Blockchains.

Allow to get practical knowledge in a wide range of quantitative methods, statistical models, and computing techniques. Learn how to extract knowledge from data and drive key decisions. I will include data analytics thinkings, trnasforming business question into dat-driven solutions, data mining, descriptive modelling, predictive modeling, text mining and network analysis. All of these principles and principles will be illustrated through applications in Marketing, fiancne , HR, Fraud, …

Allow to get practical knowledge in a wide range of quantitative methods, statistical models, and computing techniques. Learn how to extract knowledge from data and drive key decisions. I will include data analytics thinkings, trnasforming business question into dat-driven solutions, data mining, descriptive modelling, predictive modeling, text mining and network analysis. All of these principles and principles will be illustrated through applications in Marketing, fiancne , HR, Fraud, …

TERM 4: Bootcamp – Practices & Applications

This practicum will help the participant to integrate the different concepts seen during the classes into concrete experience and practices. These will be done in group.

TERM 5: In-company internship of Field Project

Back to Digital Transformation

Practical information

  • Enrolments for September 2019 are open!

  • Starting date: September 2019

  • Location: Brussels

  • Format: Full-time, day classes (60 ECTS)

  • Language: English

  • Tuition: 17,000€

  • Length: 12 months

  • Application deadline:
    > Non-EU students: 31 May 2019
    > EU students: 30 June 2019

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