MATLAB Training in Sud-Vest

This instructor-led, live training in Sud-Vest (online or onsite) is aimed at Matlab users who wish to explore or transition to Python for data analytics and visualization.

By the end of this training, participants will be able to:

• Install and configure a Python development environment.
• Understand the differences and similarities between Matlab and Python syntax.
• Use Python to extract insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

In this instructor-led, live training, participants will learn how to use Matlab to design, build, and visualize a convolutional neural network for image recognition.

By the end of this training, participants will be able to:

• Build a deep learning model
• Automate data labeling
• Work with models from Caffe and TensorFlow-Keras
• Train data using multiple GPUs, the cloud, or clusters

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

This course is structured to teach the core principles of the Systems Modeling Language (SysML), its implementation via MagicDraw/Cameo software, fundamental MBSE simulation methodologies, and industry best practices. Furthermore, the training aims to equip professionals with a solid understanding of architectural simulation, introduce the Simulation Toolkit plugin, demonstrate the simulation of various diagram types, and illustrate how to link diagram simulations to automate architectural processes.​

This comprehensive MATLAB training in Sud-Vest focuses on the simulation of wireless communications. Participants will learn to model complex systems, analyze the effects of various channels, and optimize code performance. The course is ideally suited for engineers aiming to enhance their advanced skills in signal processing and system design.