Basic MATLAB Programming Training Course

This four-day course offers foundational knowledge in image processing using Matlab. Participants will practice techniques for modifying and enhancing images, as well as extracting patterns from them. Additionally, you will learn how to construct 2D filters and apply them to images.

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

This three-day course offers a thorough introduction to the MATLAB technical computing environment. Designed for beginners and those seeking a refresher, no prior programming experience or knowledge of MATLAB is required. The course delves into themes such as data analysis, visualization, modeling, and programming. Key topics covered include:

• Navigating the MATLAB user interface
• Executing 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 using logic and flow control
• Developing functions

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

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

• Create a deep learning model
• Automate data labeling processes
• Work with models from Caffe and TensorFlow-Keras
• Train data using multiple GPUs, cloud resources, or clusters

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Combination of lecture, discussion, practical exercises, and extensive hands-on practice

In the first part of this training, we delve into the foundational aspects of MATLAB, exploring its role as both a programming language and a versatile platform. This section covers an introduction to MATLAB syntax, arrays and matrices, data visualization techniques, script development, and object-oriented principles.

In the second part, we showcase how MATLAB can be utilized for data mining, machine learning, and predictive analytics. To provide participants with a clear and practical understanding of MATLAB's capabilities, we compare its usage with other tools such as spreadsheets, C, C++, and Visual Basic.

In the third part of the training, participants will learn techniques to enhance their efficiency by automating data processing and report generation processes.

Throughout the course, participants will apply the concepts learned through hands-on exercises in a laboratory setting. By the end of the training, participants will have a comprehensive understanding of MATLAB's functionalities and will be equipped to use it for solving real-world data science problems as well as streamlining their work through automation.

Assessments will be conducted throughout the course to monitor progress.

Format of the Course

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

Note

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

This instructor-led, live training in Taiwan (online or onsite) is aimed at beginner-level developers or engineers who wish to learn how to use numerical simulation for dynamic problems using Matlab.

By the end 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 combines computation, visualization, and programming in a user-friendly environment. It provides the Financial Toolbox, which includes essential features for performing mathematical and statistical analysis of financial data, along with high-quality graphics to present the results effectively.

This instructor-led training offers an introduction to MATLAB for finance professionals. Through hands-on exercises and extensive in-lab practice, participants will delve into data analysis, visualization, modeling, and programming.

By the end of this training, participants will have a comprehensive understanding of the powerful features available in MATLAB's Financial Toolbox and will be equipped to apply these tools immediately to solve real-world problems.

Audience

• Financial professionals with prior experience using MATLAB

Format of the course

• A combination of lectures, discussions, and intensive 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, no prior programming experience or familiarity with MATLAB is required. The course delves into 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
• Working with various data types
• Automating tasks using scripts
• Writing programs that incorporate logic and flow control
• Creating functions
• Leveraging the Financial Toolbox for quantitative analysis

Object-Oriented Programming with MATLAB for Geophysics involves leveraging MATLAB’s object-oriented programming capabilities to develop well-structured, reusable, and maintainable code for geophysical data analysis and modeling.

This instructor-led, live training (available online or on-site) is designed for beginner-level MATLAB users in the field of geophysics who want to learn how to design and implement object-oriented solutions tailored for geophysical applications.

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

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

Format of the Course

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

Course Customization Options

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

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

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

In this instructor-led, live training, participants will learn how to use Matlab to construct predictive models and apply them to extensive datasets to predict future scenarios based on the available data.

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

• Create predictive models to identify patterns in historical and transactional data
• Leverage predictive modeling to recognize potential risks and opportunities
• Develop mathematical models that capture significant trends
• Utilize data from devices and business systems to enhance efficiency, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

This two-day course offers a thorough introduction to the MATLAB® technical computing environment. Designed for beginners and those seeking a refresher, the course assumes no prior programming experience or familiarity with MATLAB. Key themes such as data analysis, visualization, modeling, and programming are explored throughout the course.

The 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 best practices in MBSE. This training is also designed to provide professionals with a background behind architectural simulation, an introduction to the Simulation Toolkit plugin, the simulation of multiple diagram types, and how to tie diagram simulations together to automate the architecture.​

This course is designed for individuals interested in exploring an alternative to the commercial MATLAB software. Over three days, participants will gain a thorough understanding of navigating and utilizing the OCTAVE package for data analysis and engineering calculations. The training is suitable for both beginners and those with prior experience who wish to organize their knowledge and enhance their skills. While familiarity with other programming languages is not mandatory, it can significantly aid in learning. The course will provide numerous practical examples to demonstrate how to effectively use the program.

This instructor-led, live training in Taiwan (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 is a visual programming platform designed for the modeling, simulation, and analysis of complex, multidomain dynamic systems.