MATLAB Training in Plovdiv

Object-Oriented Programming with MATLAB for Geophysics applies 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 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.
• Extensive 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 Plovdiv (online or onsite) is designed for beginner-level developers and 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 core principles of dynamic analysis.
• Utilize Matlab to execute both analytical and numerical solutions.
• Derive motion equations through various methodologies.

In the initial phase of this training, we explore the core concepts 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, script development, and object-oriented principles.

The second section demonstrates how to leverage MATLAB for data mining, machine learning, and predictive analytics. To give participants a clear and practical understanding of MATLAB’s capabilities and advantages, we compare its usage with other common tools such as spreadsheets, C, C++, and Visual Basic.

In the third section, participants learn how to optimize their workflow by automating data processing and report generation.

Throughout the course, participants will apply the concepts learned through hands-on exercises in a lab environment. By the end of the training, participants will have a comprehensive understanding of MATLAB's capabilities and will be able to utilize it to solve real-world data science problems and streamline their work through automation.

Assessments will be conducted throughout the course to monitor progress.

Format of the Course

• The course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation.

Note

• Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange.

This instructor-led, live training in Plovdiv (online or onsite) is designed for Matlab users who want 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.

A 3-day course that takes you through the MATLAB main screens and windows including ...

• how to use matlab as a calculator and plot basic curves
• how to create your own customized functions and scripts

This four-day course covers the fundamentals of image processing using Matlab. Participants will practice techniques for modifying and enhancing images, as well as extracting patterns from them. Additionally, the course teaches how to design 2D filters and apply them to images.

Examples and exercises illustrate the use of relevant Matlab and Image Processing Toolbox functionalities 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, no prior programming background or MATLAB knowledge is required. The curriculum explores key themes including data analysis, visualization, modeling, and programming. Topics covered include:

• Navigating the MATLAB user interface
• Entering commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Managing data files
• Handling various data types
• Automating commands through scripts
• Developing programs with logical flow and control structures
• Writing functions

In this instructor-led, live training, participants will learn how to utilize Matlab to design, construct, and visualize a convolutional neural network for the purpose of image recognition.

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

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

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

MATLAB combines computation, visualization, and programming in a user-friendly environment. It features the Financial Toolbox, which provides the necessary tools for conducting mathematical and statistical analysis of financial data, along with presentation-quality graphics to display the results.

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

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

Audience

• Financial professionals who already have experience with MATLAB.

Course Format

• Combination of lectures, discussions, and intensive hands-on practice.

This course offers a thorough introduction to the MATLAB technical computing environment, alongside guidance on utilizing MATLAB for financial applications. Designed for beginners and those seeking a refresher, no prior programming experience or MATLAB knowledge is required. Key themes throughout the course include data analysis, visualization, modeling, and programming. Topics covered encompass:

• Navigating the MATLAB user interface
• Inputting commands and defining variables
• Analyzing vectors and matrices
• Visualizing data from vectors and matrices
• Manipulating data files
• Managing data types
• Automating tasks via scripts
• Developing programs 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 analysis to forecast future outcomes. This discipline combines data mining, statistics, and machine learning techniques to construct predictive models capable of anticipating upcoming events.

During this instructor-led live training, participants will discover how to utilize Matlab to construct predictive models and apply them to large-scale datasets, enabling predictions about future scenarios based on historical information.

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

• Develop predictive models to uncover patterns within historical and transactional data.
• Employ predictive modeling to pinpoint potential risks and opportunities.
• Construct mathematical models that encapsulate significant trends.
• Leverage data from devices and business systems to minimize waste, conserve time, or reduce expenses.

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• A combination of lectures, discussions, exercises, and intensive hands-on practice.

This two-day course offers a thorough introduction to the MATLAB® technical computing environment. It is designed for beginners and individuals seeking a refresher, with no assumed prior programming experience or knowledge of MATLAB. Throughout the course, key themes such as data analysis, visualization, modeling, and programming are explored in depth.

This course is structured to teach the core principles of the Systems Modeling Language (SysML), its application using MagicDraw/Cameo software, fundamental MBSE simulation techniques, and MBSE best practices. The training also equips professionals with background knowledge on architectural simulation, introduces the Simulation Toolkit plugin, covers the simulation of various diagram types, and demonstrates how to link diagram simulations to automate the architecture.​

This course is designed for individuals seeking an alternative to the commercial MATLAB package. During the three-day training, participants will gain comprehensive insights into navigating the environment and utilizing the OCTAVE package for data analysis and engineering calculations. The course caters to both beginners and those already familiar with the software who wish to systematize their knowledge and enhance their skills. While prior knowledge of other programming languages is not required, it will significantly facilitate the learning process. Throughout the course, practical examples will demonstrate how to effectively use the program.

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

This course provides comprehensive material on MATLAB as a potent simulation tool for communications. The primary objective is to introduce MATLAB not merely as a general programming language, but to emphasize the critical role its powerful capabilities play in simulation. The examples used to illustrate course content go beyond simple command execution; they often represent real-world problems.

Objective: This course is designed for software engineers engaged with Model-Based Design (MBD) technology. The training covers automotive system modeling techniques, relevant automotive standards, automatic code generation, and the creation and verification of model test harnesses. Target Audience: Software developers working for automotive suppliers.