Basic MATLAB Programming Training Course

This four-day course establishes a solid foundation in image processing using Matlab. You will learn how to modify and enhance images, as well as extract meaningful patterns from them. Additionally, you will gain skills in constructing 2D filters and applying them to image data.

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

This three-day course offers a comprehensive introduction to the MATLAB technical computing environment. It is designed for beginners and those seeking a refresher, with no prior programming experience or knowledge of MATLAB assumed. Throughout the course, we explore key themes such as data analysis, visualization, modeling, and programming. Key topics include:

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

The initial segment of this training explores the core principles of MATLAB, emphasizing its role as both a programming language and a computing platform. This section covers essential topics such as MATLAB syntax, arrays and matrices, data visualization, script creation, and object-oriented programming concepts.

In the second phase, we illustrate how to leverage MATLAB for data mining, machine learning, and predictive analytics. To highlight the efficiency and power of MATLAB, we compare its functionality with other common tools like spreadsheets, C, C++, and Visual Basic.

During the final segment, participants will learn to optimize their workflow by automating data processing and report generation tasks.

Throughout the course, participants will apply learned concepts through practical exercises in a lab setting. By the conclusion of the training, participants will possess a comprehensive understanding of MATLAB's capabilities and will be equipped to solve real-world data science challenges and streamline workflows via automation.

Progress assessments will be conducted throughout the course to monitor advancement.

Course Format

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

Note

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

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

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

• Grasp the fundamentals of dynamic analysis.
• Utilize Matlab to perform both analytical and numerical solutions.
• Derive motion equations using various approaches.

MATLAB seamlessly combines computation, visualization, and programming within an intuitive environment. It provides the Financial Toolbox, which equips users with the necessary features to conduct mathematical and statistical analysis of financial data and present the findings through high-quality graphics.

This instructor-led training introduces participants to MATLAB for finance. Through hands-on exercises and extensive in-lab practice, learners will explore data analysis, visualization, modeling, and programming.

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

Audience

• Financial professionals who already have prior experience with MATLAB

Course Format

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

This course delivers a thorough introduction to the MATLAB technical computing environment, along with an overview of applying MATLAB to financial applications. Designed for beginners and those seeking a refresher, it assumes no prior programming experience or familiarity with MATLAB. Throughout the course, key themes such as data analysis, visualization, modeling, and programming are explored. 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 using scripts
• Developing programs with logic and flow control
• Writing functions
• Leveraging 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 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.

Upon completing this training, participants will be able to:

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

Course Format

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

Customization Options

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

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, statistical methods, and machine learning techniques to construct predictive models that anticipate future events.

In this instructor-led live training, participants will learn how to utilize Matlab to build predictive models and apply them to large-scale datasets to predict future occurrences based on analyzed data.

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 risks and opportunities
• Construct mathematical models that capture significant trends
• Utilize data from devices and business systems to minimize waste, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Course Format

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

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

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

This course is designed for individuals seeking an alternative to the commercial MATLAB package. Over three days, participants receive comprehensive training on navigating the Octave environment and utilizing the Octave package for data analysis and engineering calculations. The content is suitable for both beginners and those who already possess some familiarity with the software and wish to systematize their knowledge and refine their skills. While prior experience with other programming languages is not mandatory, it can significantly ease the learning process. Through numerous practical examples, the course demonstrates how to effectively use the program in real-world scenarios.

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

Upon completing this training, participants will be capable of:

• Installing and setting up a Python development environment.
• Recognizing the similarities and differences between Matlab and Python syntax.
• Leveraging Python to extract insights from diverse datasets.
• Migrating existing Matlab applications to Python.
• Integrating Matlab and Python applications.

Simulink is a graphical computing environment designed for modeling, simulating, and analyzing multidomain dynamic systems.