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Starting from different use cases, you will learn to develop AI models yourself in a very practical way. You will thus become an AI Software Engineer who is able to develop AI models to his or her own liking. This microdegree has the ambition because possible in just 1 year, combined with a full-time job. Therefore, the content is very focused and limited to the technical part. You will learn to apply each AI technology to a relevant use case through demos and hands-on assignments.

Topics and algorithms covered include Support Vector Machines, Naive Bayes, Random Forest Trees, Convolutional Neural Networks, Generative Adversial Networks, Autoencoders....

For whom

This AI@home course is open to anyone who is at least 21 years old and/or a working student and is aimed at all those who want to start working with AI themselves. Both IT and non-ITers are welcome, but as we dive immediately into Machine & Deep Learning, you already have a (basic) programming knowledge of Python or are willing to acquire it yourself before the start of the microdegree in early September.

You choose when you want to study, we will guide you through teams. Two on-campus contact moments are also scheduled.

Distance learning is mainly delivered through our powerful LMS (learning management system). You get good-quality Dutch-language video recordings of the daytime teaching, and a lot of pratica at your disposal to work through the material at your own pace.

Why?

Machine learning and deep learning are within reach of anyone with an interest in programming or data science, thanks to powerful frameworks and cloud services.

Pulling insights from data, making predictions or automatically recognising and classifying patterns? Machine Learning and Deep Learning give a huge boost to your capabilities as a developer.

The next step?

Would you like to study artificial intelligence in even greater depth after the AI @home? Then you can still opt for the logical next step: AI@home Pro (LLMs, RAGs en Agentic AI) or "Deploying AI Solutions" master class.

General

You will take the same modules of Machine Learning and Deep Learning as regular MCT and ‘Creative Tech & AI’ students to master artificial intelligence. After this course, you will be able to develop AI models.

Machine Learning

In Machine Learning, we emphasize the conceptual understanding of how certain algorithms work. It is important to be able to choose the right machine learning algorithms, train them, evaluate them correctly and improve their performance via hyperparameter tuning. We look at the most current machine learning techniques that you can immediately use in practice:

Supervised learning where you learn from labelled data:

  • Linear (multiple) regression that allows you to predict continuous outputs. Examples include predicting stock market prices, estimating a person's age from a picture of the face, predicting risk, making predictions of sales numbers, etc.
  • Classification allows you to categorize data. Face recognition, handwriting recognition, cancer detection, predicting whether someone will click on an ad or link are just a few examples. Topics and algorithms covered include logistic regression, Support Vector Machines, Naive Bayes, Random Forest Trees and Ensemble learning.

Unsupervised learning where you extract information from unlabelled data.

  • Clustering techniques where you look for similar data. In this way, you can discover patterns, relationships and similarities in complex multi-dimensional data.
  • Dimensionality reduction allows us to transform data to its essence. Thus, data can be represented more compactly or the performance of machine learning prediction techniques can be increased.

Neural Networks

  • Inspired by how the brain works allow us to extract insights from data that were not possible until recently. In the machine learning module, we look at its conceptual workings and build neural networks for regression and classification. This lays the foundation for the deep learning module that builds on this.

In this module, you will learn the concepts of a number of machine learning algorithms and especially how to practically apply them to solve ML problems.

It also lays the foundation for the Deep Learning module that follows on from this.

Deep Learning

The deep learning module picks up where the Machine Learning module left off, namely with neural networks.

  • Introduction to Deep Neural Networks
  • Convolutional Neural Networks (CNN)
  • Auto encoders en restricted Bolzmann machines: can reconstruct lost or damaged data but can also be used to generate music or make suggestions.
  • Generative Adversarial Networks (GAN). Are used for e.g. image generation, predicting which drug will work for certain symptoms ... the first steps in to Generative AI.
  • Recommendation systems to generate personalised recommendations.
  • Neural networks with memory: Recursive Neural Networks (RNN) and Long Short-term memory networks (LSTM): applications include natural language processing and sentiment analysis..
  • Reinforcement learning: the algorithm learns by interacting with the environment.
Course unit descriptions for this study programme

Location

You take this course from home, i.e. online. Twice a semester, you come to our campus in Kortrijk (not compulsory).

Duration

This cours takes about 10 Months

Credits

This course consists of 12 credits, 6 per semester. Per semester, this corresponds to +/- 150 hours of study time. However, the latter strongly depends on your prior knowledge.

Evaluation

50% of your score depends on your practical assignments. A selection of these assignments is made and checked for quality of execution. You earn the other 50% through a theoretical exam at the end of the semester.

Government subsidies

This training is eligible for Flemish "Opleidingsverlof" with the following code ODB-X01091.

This training qualifies for support through the SME portfolio (KMO portefeuille) under the theme profession-specific competences (recognition number: DV.O241438). Application for support must be made within 14 days of the start of training. More information can be found at www.kmo-portefeuille.be.

Kostprijs

The cost of this program is 471 euros.

Enrolment

Enrolment for the coming academic year starts on July 1st. You can enrol at one of the Info Days on campus, by appointment at the student secretariat of the Howest campus where your programme takes place, or by using the online registration system.

Which documents will you need?

  • A copy of your ID (front and back) will be requested during online enrolment.
  • You will also need to upload a copy of your (higher education) diploma.

Online enrolment

After you've registered

  • After completing the online application, you will receive an e-mail with all the information needed to complete your enrolment.
  • Once your file has been checked and processed by Howest, you will receive your contract and the request for payment of tuition fees and extra study costs electronically.

Troeven van de opleiding

Link to the real professionals

During a training at Howest Academy, you will work with cases and challenges from your professional field. The Howest teaching team is supplemented with leading guest speakers and experts in the field. This way, we guarantee a practical translation of the learning content offered.

Expert professors

When you choose to study at Howest Academy, you choose quality. Our teachers are not only content experts in their field, they are also didactically strong to translate the course content into achievable learning experiences. That way, you can achieve your set goals in combination with your work and family.

Always up-to-date

Not only does this course respond to current changes, it is also one step ahead through its link with the hands-on applied research conducted at Howest.

Official certificate from Howest

Successful completion of this microdegree leads to the acquisition of official credits and a certificate from the college.

Nieuws

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Register now!

Have you decided? We look forward to welcoming you to our Howest community! 
You can find all information about registering via the link below.

Apply now

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FAQ

Vind je niet wat je zoekt of heb je specifieke vraag over deze opleiding. Neem gerust contact met ons op.

Johan De Gelas

Johan De Gelas

Academic Director

Contact

Completing the online registration implies that you are officially enrolled and commits you to paying the registration fee. After your file is processed, you will receive an email with an invoice for payment of the registration fee.

Most advanced programmes (such as micro degrees and post-graduate programmes) are not eligible for scholarships or reduced fees. That type of financial assistance is reserved for students within the standard programmes (bachelor's). However, there are other possibilities offered by the Flemish government such as Flemish educational allowance, KMO-portefeuille and study vouchers.

Yes, it is possible. Please send your account number and billing details to howestacademy [at] howest.be (howestacademy[at]howest[dot]be). The refund for the originally paid registration fee will only be made after registration of payment with the SME-wallet. You will therefore temporarily have a double payment pending.

If your training is partially or fully funded through financial assistance (SME, Flemish training leave, Flemish educational allowance, Flemish training vouchers), it is important to check the terms of the financial assistance programme concerning compulsory attendance. Students are responsible for having their attendance formally registered by the lecturers.

The coordinator of your course will indicate which platform will be used for short-term courses. For long-term programmes, your course material can be found on leho.howest.be. You can log in with the details you received from the registrar’s office after enrolment.

Send an e-mail to howestacademy [at] howest.be (howestacademy[at]howest[dot]be) and you will get a quick reply.

For short-term postgraduate courses, direct registration via the webpage is final and binding. For diploma and credit courses such as bachelor’s, associates and microdegrees, pre-registration is not binding, but it assures you a place in the programme.

  • For associates degree:
    You are officially enrolled once you have completed your pre-registration online and signed it digitally. After processing and approval of your online registration by the registrar’s office, you will receive login details and an invoice for payment of the registration fee.
  • For microdegrees:
    You are officially enrolled after your pre-registration has been processed by the student registrar and after you have signed your programme contract. This can be done manually or digitally via the digital student learning platform: https://leho.howest.be/ (shortcut at the bottom -> ibamaflex -> important information).

Payment of the registration fee must be made no later than 1 October or - if the course starts at another time - within 15 days of registration. For payments made by invoice, the latest payment date mentioned on the invoice applies. Only in exceptional cases will instalment payments be allowed and only if an instalment plan has been submitted and agreed to by Howest's financial officer. Please contact us at howestacademy [at] howest.be (howestacademy[at]howest[dot]be) for more information.

Ben je ingeschreven voor een bachelor-na-bachelor, een postgraduaat, een micro degree en/of een navorming? Dan kom je niet in aanmerking voor financiële ondersteuning in je studiekosten.

Heb je hier toch vragen rond? Neem contact op met de sociale dienst van Stuvo