2026 - MATLAB Course on Artificial Intelligence Algorithms and Machine Learning Techniques

Organizer: Prof. M. Celli

Teacher: Dr. Paolo Panarese, EDU Academic Team - Principal Education Customer Success Engineer, The MathWorks Srl.

 The Mathworks webpage relative to the event is here.

A MathWorks account is required. To create your own MathWorks account click here. Please remember that the course is held in BYOD (Bring Your Own Device) mode thus the students must bring their own laptop (the class is equipped with individual sockets).

At the end of the training there will be a final evaluation. For any question/issue about the course please contact Prof.  michele.celli3@unibo.it

Dates, topics, and place. Four modules are planned in Aula 0.5 (viale Risorgimento 2, Bologna, ground floor) for a total of 14 hours (no online streaming nor recording are prescribed):

1. day 1 13/7 morning 9:00 – 12:30: Review of Machine Learning
2. day 1 13/7 afternoon 14:00 – 17:30: Deep Learning
3. day 2 14/7 morning 9:00 – 12:30: Deep Learning for Model-Based Design
4. day 2 14/7 afternoon 14:00 – 17:30: Advanced Deep Learning

Mandatory prerequisites: Please note that the course organizers require as mandatory the following online MathWorks preliminary courses, to be attended by the students before the lectures:

• MATLAB Onramp
• Simulink Onramp
• Deep Learning Onramp
• at least 1 onramp among:
• Machine Learning Onramp
• Image Processing Onramp -> Computer Vision Onramp
• Explore Convolutional Neural Networks
• Signal Classification with Deep Learning
• Object Detection with Deep Learning
• Simscape Onramp -> Multibody Simulation Onramp

 Each online MathWorks preliminary course completed will give you a certificate. Four certificates, thus four preliminary courses, are necessary for the registration. You must upload the certificates by filling the following form.

 https://forms.gle/RRJnGruRQrWTQWz2A

 The deadline for filling the form (thus for the registration) is 02/07/2026. The days after 02/07/2026, you will receive an email confirming the reception of the certificates

Software installation. Running examples used during the workshop will require the latest release of MATLAB R2026a, including all products and Deep Learning add-ons. We recommend you install, on your laptop, the complete license and the following Deep Learning Add-ons to ensure any dependency requirements (available from MATLAB File Exchange):

• Deep Learning Toolbox Model for AlexNet Network
• Deep Learning Toolbox Model for GoogLeNet Network
• Deep Learning Toolbox Model for VGG-16 Network
• Deep Learning Toolbox Model for ResNet-50 Network
• Deep Learning Toolbox Model for SqueezeNet Network
• Deep Learning Toolbox Converter for ONNX Model Format
• Deep Learning Toolbox Converter for PyTorch Models 
• Deep Learning Toolbox Converter for TensorFlow Models
• AI Verification Library for Deep Learning Toolbox
• Deep Learning Toolbox Model Compression Library
• MATLAB Coder Interface for Deep Learning
• Automated Visual Inspection Library for Computer Vision Toolbox
• Reduced Order Modeler for MATLAB

Possible projects post training. At the end of the training students will have the possibility to apply for one capstone projects:

• Artificial Intelligence
• Autonomous Vehicles
• Drones
• Industry 4.0
• Robotics

The course is structured into 14 hours of lessons through 4 modules of 3.5 hours each. The lessons will take place in the Informatic laboratory with the use of the MATLAB software. The aim of the course is to introduce students to programming techniques that are useful for addressing four main topics: image processing, machine learning, deep learning, and Simulink. To participate in the face-to-face lessons, completing 3 preparatory courses on the MATLAB e-learning platform is mandatory. These modules are intended to provide an introduction to basic programming in the Matlab environment. A final test is planned in order to verify the candidate's proficiency.  / Il corso è strutturato in 14 ore di lezione attraverso 4 moduli da 3,5 ore ciascuno. Le lezioni si svolgeranno nel Laboratorio Informatico con l'utilizzo del software MATLAB. Lo scopo del corso è introdurre gli studenti alle tecniche di programmazione utili per affrontare quattro argomenti principali: elaborazione delle immagini, machine learning, deep learning e Simulink. Per partecipare alle lezioni in presenza è obbligatorio completare 3 corsi propedeutici sulla piattaforma e-learning MATLAB. Questi moduli hanno lo scopo di fornire un'introduzione alla programmazione di base nell'ambiente Matlab. È prevista una prova finale per verificare le competenze del candidato.