MATLAB Training in Milan

Object-Oriented Programming with MATLAB for Geophysics involves applying MATLAB’s OOP features to develop structured, reusable, and maintainable code for geophysical data analysis and modeling.

This instructor-led, live training (available online or onsite) is designed for beginner-level MATLAB users in 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:

• Understand the fundamentals of object-oriented programming in MATLAB.
• Create and work with classes, properties, and methods for geophysical data handling.
• Apply OOP techniques to structure geophysical modeling and analysis workflows.
• Enhance code reusability, scalability, and clarity for geoscience projects.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This instructor-led, live training in Milan (online or onsite) is designed for beginner-level developers or engineers who wish to learn how to apply numerical simulation for dynamic problems using Matlab.

Upon completion of this training, participants will be able to:

• Grasp the core principles of dynamic analysis.
• Utilize Matlab to execute analytical and numerical solutions.
• Derive motion equations through various methodologies.

In the initial phase of this training, we explore the core principles of MATLAB, highlighting its dual role as both a programming language and a comprehensive platform. The curriculum introduces MATLAB syntax, arrays and matrices, data visualization techniques, script development, and object-oriented concepts.

The second segment demonstrates how to leverage MATLAB for data mining, machine learning, and predictive analytics. To clearly illustrate MATLAB’s capabilities and efficiency, we compare its workflow with other common tools such as spreadsheets, C, C++, and Visual Basic.

In the final segment, participants will learn to streamline their workflows by automating data processing and report generation tasks.

Throughout the course, participants will apply their learning through hands-on exercises in a lab setting. By the conclusion of the training, participants will possess a deep understanding of MATLAB’s features, enabling them to address real-world data science challenges and automate their work processes effectively.

Progress will be assessed continuously throughout the course.

Course Format

• The course combines theoretical instruction with practical exercises, including case studies, sample code analysis, and hands-on implementation.

Note

• Practice sessions utilize pre-arranged sample data report templates. If you have specific needs, please contact us to arrange customization.

This instructor-led live training in Milan (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 obtain insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This 3-day course guides you through the primary MATLAB interfaces and windows, covering:

• using MATLAB as a calculator and plotting fundamental curves
• developing custom functions and scripts

This four-day course covers the fundamental concepts of image processing using Matlab. Participants will practice techniques to modify and enhance images, as well as extract patterns from them. Additionally, the course teaches how to construct 2D filters and apply them to images.

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

This three-day program offers a thorough introduction to the MATLAB technical computing environment. Designed for beginners and those seeking a refresher, the course assumes no prior programming experience or familiarity with MATLAB. Throughout the sessions, key themes such as data analysis, visualization, modeling, and programming are explored. Key topics covered include:

• Navigating the MATLAB user interface
• Executing commands and creating variables
• Analyzing vectors and matrices
• Visualizing data from vectors and matrices
• Manipulating data files
• Managing data types
• Automating tasks via scripts
• Developing programs with logic and flow control
• Creating functions

In this guided, hands-on training session, participants will discover how to utilize Matlab to design, construct, and visualize convolutional neural networks for image recognition tasks.

Upon completing this training, participants will be capable of:

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

Audience

• Developers
• Engineers
• Domain experts

Course Format

• A blend of lectures, discussions, exercises, and extensive practical application

MATLAB combines computation, visualization, and programming in a user-friendly environment. It provides the Financial Toolbox, which includes the necessary features to conduct mathematical and statistical analysis of financial data, followed by the display of results using presentation-quality graphics.

This instructor-led training offers an introduction to MATLAB for finance. Participants will explore data analysis, visualization, modeling, and programming through hands-on exercises and extensive in-lab practice.

By the end of this training, participants will have a comprehensive understanding of the powerful features within MATLAB's Financial Toolbox and will have gained the necessary practice to immediately apply them to solve real-world problems.

Audience

• Financial professionals with prior experience using MATLAB

Course Format

• Part lecture, part discussion, with heavy emphasis on hands-on practice

This course offers a thorough introduction to the MATLAB technical computing environment, alongside an overview of its application in financial contexts. Designed for beginners and those seeking a refresher, it assumes no prior programming background or familiarity with MATLAB. The curriculum covers key themes such as data analysis, visualization, modeling, and programming. Key topics include:

• Navigating the MATLAB user interface
• Inputting commands and managing variables
• Analyzing vectors and matrices
• Visualizing data contained in vectors and matrices
• Managing data files
• Handling various data types
• Automating commands using scripts
• Programming with logical structures and flow control
• Creating functions
• Leveraging the Financial Toolbox for quantitative analysis

MATLAB is a numerical computing environment and programming language developed by MathWorks.

Predictive analytics involves leveraging data analytics to forecast future outcomes. This approach combines data with data mining, statistics, and machine learning methods to construct predictive models capable of anticipating upcoming events.

During this instructor-led live training, participants will learn how to utilize Matlab to develop predictive models and apply them to large datasets for forecasting future trends based on historical information.

Upon completion of this training, participants will be able to:

• Develop predictive models to analyze patterns in historical and transactional data
• Employ predictive modeling to pinpoint potential risks and opportunities
• Construct mathematical models that effectively capture significant trends
• Leverage data from devices and business systems to minimize waste, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

This intensive two-day program offers a thorough overview of the MATLAB® technical computing environment. Designed for beginners as well as those seeking a refresher, the course assumes no previous programming experience or familiarity with MATLAB. Key topics such as data analysis, visualization, modeling, and programming are covered extensively throughout the session.

This course is designed to teach the fundamentals of the Systems Modeling Language (SysML), its application via MagicDraw/Cameo software, basic Model-Based Systems Engineering (MBSE) simulation techniques, and MBSE best practices. The training also equips professionals with a background in architectural simulation, introduces the Simulation Toolkit plugin, demonstrates the simulation of various diagram types, and shows how to integrate diagram simulations to automate architecture.​

This course is designed for individuals seeking an open-source alternative to the commercial MATLAB package. Over the course of three days, participants will gain comprehensive insights into navigating the Octave environment and utilizing the software for data analysis and engineering calculations. The training is suitable for both beginners and experienced users who wish to systematize their knowledge and refine their skills. While prior knowledge of other programming languages is not required, it can significantly accelerate the learning process. The course emphasizes practical application through numerous real-world examples.

Simulink serves as a graphical computing environment designed for the modeling, simulation, and analysis of multidomain dynamic systems.

This course provides comprehensive material on utilizing MATLAB as a robust simulation tool for communications. The primary objective is to introduce MATLAB not merely as a general programming language, but to emphasize its powerful capabilities for simulation. The examples used to illustrate the course material go beyond simple command usage; they often address real-world engineering problems.

Objective: This training is designed for Software Engineers engaged in Model-Based Design (MBD) technology. The curriculum encompasses modeling techniques for automotive systems, relevant automotive standards, automated code generation, and the construction and verification of test harnesses for models. Audience: Software developers working with automotive suppliers.