Dynamic Analysis Using Matlab Training Course

This three-day course provides an in-depth exploration of the primary MATLAB interface and workspace elements. Key topics include:

• Utilizing MATLAB for calculations and generating fundamental plots
• Developing custom functions and scripts tailored to specific needs

This four-day course covers the foundational concepts of image processing using Matlab. You will learn how to manipulate and enhance images, as well as extract patterns from them. Additionally, you will gain skills in constructing 2D filters and applying them to images.

Throughout the analysis process, examples and exercises illustrate the use of relevant Matlab and Image Processing Toolbox functionalities.

This three-day program offers a thorough introduction to the MATLAB technical computing environment. It is designed for beginners as well as those seeking a refresher course. No previous programming experience or knowledge of MATLAB is required. The course explores key themes such as data analysis, visualization, modeling, and programming. Key topics covered include:

• Navigating the MATLAB user interface
• Entering commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Working with data files
• Working with data types
• Automating commands using scripts
• Writing programs with logic and flow control
• Writing functions

In this live, instructor-led training, participants will master the use of Matlab to design, construct, and visualize convolutional neural networks (CNNs) for image recognition tasks.

Upon completion of this training, participants will be capable of:

• Constructing deep learning models
• Automating the data labeling process
• Utilizing models developed in Caffe and TensorFlow-Keras
• Training data across multiple GPUs, cloud environments, or clusters

Target Audience

• Developers
• Engineers
• Domain experts

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

MATLAB seamlessly integrates computation, visualization, and programming within an intuitive environment. It includes the Financial Toolbox, providing the essential features for conducting mathematical and statistical analysis on financial data, along with the ability to present results through high-quality graphics.

This instructor-led training introduces participants to MATLAB in the context of finance. The course covers data analysis, visualization, modeling, and programming through practical exercises and extensive in-lab practice.

Upon completion of this training, participants will have a comprehensive understanding of the powerful capabilities within MATLAB's Financial Toolbox and will possess the practical skills required to apply these tools immediately to solve real-world problems.

Audience

• Financial professionals who already have experience with MATLAB

Course Format

• A blend of lectures and discussions, with a strong emphasis on hands-on practice

This course offers a thorough introduction to the MATLAB technical computing environment, along with a foundational guide to utilizing MATLAB for financial applications. It is designed for beginners and those seeking a refresher. No previous programming experience or familiarity with MATLAB is required. Throughout the course, we explore key themes including data analysis, visualization, modeling, and programming. Key topics covered include:

• Navigating the MATLAB user interface
• Inputting commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Managing data files
• Understanding data types
• Automating tasks via scripts
• Developing programs with logic and flow control
• Creating functions
• Utilizing the Financial Toolbox for quantitative analysis

Object-Oriented Programming with MATLAB for Geophysics leverages MATLAB's OOP capabilities to develop structured, reusable, and maintainable code for geophysical data analysis and modeling.

This instructor-led live training, available either online or onsite, targets beginner-level MATLAB users in the field of geophysics who want to learn how to design and implement object-oriented solutions for geophysical applications.

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

• Grasp the fundamentals of object-oriented programming within MATLAB.
• Create and utilize classes, properties, and methods for handling geophysical data.
• Apply OOP techniques to structure geophysical modeling and analysis workflows.
• Improve code reusability, scalability, and clarity for geoscience projects.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training session for this course, please contact us to arrange it.

This intensive two-day course offers a thorough introduction to the MATLAB® technical computing environment. Designed for both novice users and professionals seeking a refresher, it assumes no prior programming background or familiarity with MATLAB. The curriculum delves into key themes including data analysis, visualization, modeling, and programming techniques.

This course is designed to teach the fundamentals of the Systems Modeling Language (SysML), its application via the MagicDraw/Cameo software, basic Model-Based Systems Engineering (MBSE) simulation techniques, and MBSE best practices. Additionally, it equips professionals with background knowledge on architectural simulation, introduces the Simulation Toolkit plugin, demonstrates the simulation of various diagram types, and explains how to link diagram simulations to automate architectural processes.​

This instructor-led, live training in Czech Republic (online or onsite) is aimed at Matlab users who wish to explore and 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 obtain insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

Elevate automotive engineering proficiency through this advanced Simulink training, which integrates theoretical models of multidomain dynamic systems with practical examples using Simulink/Stateflow verifiers, Reactis tools, and Matelo applications. Tailored for automotive systems engineers, control specialists, and MATLAB/Simulink professionals aiming to master complex automotive modeling, this course provides hands-on expertise in solver selection, subsystem simulation parameters, and system verification. Participants will learn to build reliable, high-performance automotive control models, thereby accelerating vehicle development cycles.

This course provides comprehensive material on MATLAB, a powerful simulation tool for communications. The primary objective is to introduce MATLAB not merely as a general programming language, but to emphasize its role as an exceptionally powerful simulation environment. The examples used to illustrate the course material are not simple demonstrations of MATLAB commands; instead, they often represent real-world problems.

Objective: This course is designed for software engineers utilizing Model-Based Design (MBD) technology. The curriculum encompasses automotive system modeling techniques, automotive standards, automated code generation, and the construction and verification of model test harnesses. Target Audience: Software developers working for automotive suppliers.