Dynamic Analysis Using Matlab Training Course

This three-day course guides participants through the primary interfaces of MATLAB, covering essential topics such as...

• utilizing MATLAB as a calculator and generating basic plots
• developing custom functions and scripts

This four-day course offers foundational training in image processing with Matlab. You will learn how to modify and enhance images, as well as extract patterns from them. Additionally, you will gain skills in constructing 2D filters and applying them to images.

Examples and exercises throughout the course illustrate the use of relevant Matlab and Image Processing Toolbox functionalities during the analysis process.

This three-day program delivers 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. Throughout the course, we explore key themes of 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
• Handling various data types
• Automating tasks with scripts
• Writing programs with logic and flow control
• Defining and using 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 parts. The first section introduces MATLAB's core concepts, covering its role as both a programming language and a computing platform. Topics include MATLAB syntax, arrays and matrices, data visualization, 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 effectiveness and versatility, we compare its approach with other common tools such as spreadsheets, C, C++, and Visual Basic.

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

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

Progress assessments will be conducted throughout the course.

Course Format

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

Note

• Practice sessions utilize pre-arranged sample data and report templates. If you have specific requirements, please contact us to arrange custom materials.

MATLAB seamlessly integrates 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 analyses on financial data and present the results using high-quality graphics.

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

Upon completion of this training, participants will have a deep understanding of the powerful capabilities within MATLAB's Financial Toolbox and will have gained sufficient practical experience to immediately apply these tools to solve real-world financial problems.

Audience

• Financial professionals who already have prior 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 an overview of using MATLAB for financial applications. Designed for beginners and those seeking a refresher, it assumes no prior programming experience or familiarity with MATLAB. The curriculum explores key themes such as data analysis, visualization, modeling, and programming. Topics covered include:

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

Object-Oriented Programming with MATLAB for Geophysics leverages MATLAB's OOP capabilities to develop organized, reusable, and maintainable code tailored for geophysical data analysis and modeling.

This instructor-led live training, available both online and onsite, is designed for 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 core principles of object-oriented programming in MATLAB.
• Construct 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 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 analytics to forecast future outcomes. This discipline integrates data with data mining, statistical analysis, and machine learning methodologies to construct predictive models capable of anticipating future events.

In this instructor-led live training, participants will acquire the skills to utilize Matlab for developing predictive models and applying them to large-scale datasets to anticipate future trends based on historical data.

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

• Develop predictive models to analyze patterns within historical and transactional data
• Employ predictive modeling techniques 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 blend of lectures, discussions, exercises, and extensive hands-on practice

This two-day program offers a thorough introduction to the MATLAB® technical computing environment. Designed for beginners and those seeking a refresher, no prior programming experience or familiarity with MATLAB is required. The course covers key themes such as data analysis, visualization, modeling, and programming throughout its duration.

This course is structured to teach the core principles of the Systems Modeling Language (SysML) and its application using MagicDraw/Cameo software, alongside fundamental Model-Based Systems Engineering (MBSE) simulation techniques and best practices. The training aims to equip professionals with a comprehensive understanding of architectural simulation, introduce the Simulation Toolkit plugin, demonstrate the simulation of various diagram types, and illustrate how to link diagram simulations to automate architectural workflows.​

This course is designed for individuals seeking a free, open-source alternative to the commercial MATLAB software. Over three days, participants will gain comprehensive insights into navigating the Octave environment and utilizing it for data analysis and engineering computations. The training is suitable for both beginners and those who already have some familiarity with the software and wish to systematize their knowledge and refine their skills. While prior experience with other programming languages is not a prerequisite, it can significantly accelerate the learning process. Through numerous practical examples, the course demonstrates effective ways to apply the program in real-world scenarios.

This instructor-led live training in South Korea (online or onsite) is designed for 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.

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