Basic MATLAB Programming Training Course

This four-day course provides the foundational knowledge of image processing using Matlab. You will practice how to change and enhance images and even extract patterns from the images. You will also learn how to build 2D filters and apply them on the images.

Examples and exercises demonstrate the use of appropriate Matlab and Image Processing Toolbox functionality throughout the analysis process.

This three-day program offers a thorough introduction to the MATLAB technical computing environment. Designed for beginners and those seeking a refresher, it assumes no prior programming experience or familiarity with MATLAB. The course explores key themes such as 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
• Handling data files
• Managing data types
• Automating tasks with scripts
• Developing programs with logic and control flow
• Creating functions

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 training is divided into three key sections. The first part explores the core fundamentals of MATLAB, examining its role as both a programming language and a development platform. Key topics include an introduction to MATLAB syntax, arrays and matrices, data visualization techniques, script development, and object-oriented programming principles.

The second section demonstrates how to leverage MATLAB for data mining, machine learning, and predictive analytics. To highlight MATLAB’s unique approach and capabilities, we draw comparisons with other tools such as spreadsheets, C, C++, and Visual Basic, offering participants a clear and practical perspective.

In the final part, participants will learn how to streamline their workflow by automating data processing and report generation.

Throughout the course, participants will reinforce their learning through hands-on exercises in a lab environment. By the end of the training, they will have a comprehensive understanding of MATLAB’s capabilities, enabling them to solve real-world data science problems and automate their work effectively.

Progress will be assessed throughout the course to ensure learning objectives are met.

Format of the Course also allows for the evaluation of participants.

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

Note

• Practice sessions utilize pre-arranged sample data report templates. For specific requirements, please contact us to make arrangements.

This instructor-led, live training in France (online or onsite) targets beginner-level developers or engineers seeking to learn how to apply numerical simulation for dynamic problems using Matlab.

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

• Understand the fundamentals of dynamic analysis.
• Use Matlab to perform analytical and numerical solutions.
• Derive motion equations using different approaches.

MATLAB seamlessly integrates computation, visualization, and programming within a user-friendly environment. It provides the Financial Toolbox, featuring essential tools for conducting mathematical and statistical analysis of financial data, along with the ability to display results through high-quality graphics.

This instructor-led training offers an introduction to using MATLAB in the finance sector. Through hands-on exercises and extensive in-lab practice, participants will explore data analysis, visualization, modeling, and programming.

Upon completion, participants will possess a comprehensive understanding of the powerful features within MATLAB's Financial Toolbox and will have acquired the necessary practical experience to immediately apply them to solve real-world problems.

Audience

• Financial professionals who already have experience with MATLAB

Course Format

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

This course offers a thorough introduction to the MATLAB technical computing environment, alongside a guide to utilizing MATLAB for financial applications. Designed for beginners and those seeking a refresher, it assumes no prior programming experience or familiarity with MATLAB. Throughout the course, we explore key themes such as data analysis, visualization, modeling, and programming. Topics covered include:

• Navigating the MATLAB user interface
• Inputting commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Handling data files
• Working with various data types
• Automating tasks with scripts
• Writing programs with logic and flow control
• Developing functions
• Leveraging the Financial Toolbox for quantitative analysis

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

This instructor-led live training, available online or onsite, targets beginner-level MATLAB users in the geophysics field 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 in 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 also allows for the evaluation of participants.

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

Course Customization Options

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

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

Predictive analytics involves leveraging data analysis to forecast future outcomes. This process combines data with data mining, statistical methods, and machine learning techniques to develop predictive models that anticipate future events.

In this instructor-led live training, participants will learn how to utilize MATLAB to construct predictive models and apply them to large-scale datasets to forecast future scenarios based on data insights.

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 identify potential risks and opportunities
• Construct mathematical models that 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

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

This two-day program offers a thorough introduction to the MATLAB® technical computing environment. It is designed for beginners and individuals seeking a refresher. No prior programming experience or familiarity with MATLAB is required. The course explores key themes including data analysis, visualization, modeling, and programming.

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

This course is designed for individuals seeking an alternative to the commercial MATLAB software package. The three-day training delivers comprehensive guidance on navigating the environment and leveraging the Octave package for data analysis and engineering computations. It caters to both beginners and experienced users looking to systematize their knowledge and enhance their skills. While prior knowledge of other programming languages is not mandatory, it significantly aids in the learning process. Through numerous practical examples, the course demonstrates how to effectively utilize the program.

This instructor-led live training in France (online or onsite) is designed for Matlab users who wish to explore or transition to Python for data analytics and visualization.

Upon completion 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.

Simulink serves as a graphical programming environment designed for modeling, simulating, and analyzing multidomain dynamic systems.