Introduction to Image Processing 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 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

This training is divided into three segments. The first section introduces the core concepts of MATLAB, exploring its role as both a programming language and a comprehensive platform. Key topics include an introduction to MATLAB syntax, handling 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 the efficiency and power of MATLAB, we compare its workflow with other tools such as spreadsheets, C, C++, and Visual Basic.

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

Throughout the course, participants will apply theoretical knowledge through hands-on exercises in a lab environment. By the conclusion of the training, participants will possess a solid understanding of MATLAB’s capabilities and will be equipped to use it for solving real-world data science challenges and streamlining operations through automation.

Assessments are integrated throughout the course to monitor progress.

Course Format

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

Note

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

This instructor-led, live training session, offered in Czech Republic (online or onsite), targets beginner-level developers and engineers seeking to learn how to employ numerical simulation for dynamic problems using Matlab.

By the conclusion of this training, participants will be capable of:

• Comprehending the basics of dynamic analysis.
• Utilizing Matlab for analytical and numerical solutions.
• Deriving equations of motion via diverse methods.

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.

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

Predictive analytics is the process of using data analytics to make predictions about the future. This process uses data along with data mining, statistics, and machine learning techniques to create a predictive model for forecasting future events.

In this instructor-led, live training, participants will learn how to use Matlab to build predictive models and apply them to large sample data sets to predict future events based on the data.

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

• Create predictive models to analyze patterns in historical and transactional data
• Use predictive modeling to identify risks and opportunities
• Build mathematical models that capture important trends
• Use data from devices and business systems to reduce waste, save time, or cut costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

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 course is designed for individuals seeking an alternative to the commercial MATLAB package. Over the course of three days, participants will gain comprehensive insights into navigating the environment and utilizing the Octave package for data analysis and engineering calculations. The training caters to both beginners and those with prior knowledge who wish to systematize their understanding and refine their skills. While knowledge of other programming languages is not a prerequisite, it will significantly enhance the learning process. Through numerous practical examples, the course demonstrates how to effectively utilize the program.

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.

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