Education

The Postgraduate Certificate: Artificial Intelligence in Business and Industry aims to give engineers, computer scientists and other professionals the opportunity to specialise in the field of AI. This training allows professionals to acquire in one year a solid academic knowledge of AI, as well as insight into the domains of image and language (computer vision/NLP) and business aspects of AI.  

What can you find on this webpage?

Our (future) students can find information about the programme, admission requirements, objectives and evaluation. 

 

All other information with regard to the study programme can be found at the website of the Postgraduate Certificate: Artificial Intelligence in Business and Industry

 

Objectives

The Postgraduate Certificate: Advanced Programme on Artificial Intelligence in Business and industry allows participants to strongly upgrade their previously obtained master's degree. The main objective of this programme is to equip participants with the essential academic knowledge and skills in the field of artificial intelligence, that are currently required by society and the labour market. Thus, the postgraduate programme does not aim to form "practitioners", as the scope of the programme is too limited for this purpose. However, the training does provide the basic knowledge, which can be used in a subsequent phase to apply algorithms and techniques to one's own context, niche, company.


After successful completion of the Advanced Programme on Artificial Intelligence in Business and Industry, these are the achieved objectives:

Domain specific

1. Have the required knowledge and understanding of Artificial Intelligence techniques and tools to be able to engage in professional activities in areas such as Big Data Analysis, Speech and Language Technology, Logistics, Robotics, or other application domains of Artificial Intelligence.

2. Having an advanced understanding of how AI can be applied in an industrial context and how AI can contribute to the business goals of an organisation.

3. Being able to critically evaluate AI systems and technologies from both a technological and a business perspective.

4. Acting with a research attitude, which includes creativity, critical reflection and curiosity.

5. Designing innovation and operation-oriented systems, products, services and processes, integrating and evaluating them in the business context.

6. Acting with a master-level engineering attitude within the discipline-specific context of Artificial Intelligence, which includes precision, taking process ownership, and justifying choices by means of application-oriented arguments.

Training specific

MMK1 Scientific-disciplinary knowledge and comprehension in the field of Artificial Intelligence

1. Students have scientific-disciplinary knowledge and comprehension in the field of Artificial Intelligence: they understand how state-of-the-art AI systems are built, how they are used in practice, how they lead to added value from a business perspective and what the relevant legal and ethical considerations are.

MMK2 Gaining in-depth knowledge and comprehension, including the ability to develop relevant prototypes or proof-of-concepts, in at least one of the following disciplines in Artificial Intelligence:
machine learning, deep learning, knowledge representation, computer vision, audio processing, natural language processing, search and optimisation. Gaining in-depth knowledge and comprehension of at least one of the following application domains of Artificial Intelligence: health, education, logistics, manufacturing, robotics.

MMI1 Problem analysis and solving

1. Students adopt a systematic or innovative approach, using their analytical skills, when solving complex practical engineering problems in the domain of Artificial Intelligence
MMI2 Design and/or development

2. Students can design, implement and test an Artificial Intelligence product or service, keeping the concrete context in mind.

MMI3 Application-oriented research

3. Students demonstrate the ability to act with a creative, precise, inquisitive and critical research attitude by formulating an application-oriented research problem in the domain of Artificial Intelligence, and by choosing and applying the appropriate methodologies to carry out the necessary experiments, including the critical interpretation of the results.

MMG3 Critical thinking

3. Students reflect critically on their choices, actions and obtained results, and can justify the choices made.
MMG4 Working in a team in different roles

4. Students function as a loyal member within an interdisciplinary team, act independently and in a responsible way, helping the team to achieve its goals.

MMG5 Professionalism

5. Students work accurately, show curiosity and perseverance, respect deadlines and commitments, are aware of the limitations of own competences. The students act in a result-oriented way, pay attention to planning and to technical, economical and societal constraints like sustainability. The students can estimate risks and feasibility of a proposed approach or solution and obtain effective solutions.

Educational quality of the study programme

Here you can find an overview of the results of the COBRA internal quality assurance method.

Educational quality at study programme level

Blueprint

Educational quality at university level

• Consult the documents on educational quality available at university level.

More information?

• More information on the educational quality at KU Leuven
• More information on the available documents