Basic MATLAB Programming Training Course

This four-day course offers foundational training in image processing using Matlab. You will gain hands-on experience in modifying and enhancing images, as well as extracting patterns from them. Additionally, you will learn to design 2D filters and apply them to images.

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

This three-day course offers 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, key themes such as data analysis, visualization, modeling, and programming are explored. Key topics covered include:

• Navigating the MATLAB user interface
• Entering commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Handling data files
• Working with data types
• Automating commands via scripts
• Writing programs with logic and flow control
• Creating 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 key segments. The first segment introduces the core fundamentals of MATLAB, exploring its role as both a programming language and a comprehensive platform. Topics covered include an introduction to MATLAB syntax, arrays and matrices, data visualization techniques, script development, and the principles of object-oriented programming.

The second segment demonstrates how to leverage MATLAB for data mining, machine learning, and predictive analytics. To help participants clearly appreciate MATLAB's capabilities and efficiency, we draw comparisons between using MATLAB and other common tools such as spreadsheets, C, C++, and Visual Basic.

In the third segment, participants will learn how to enhance their workflow efficiency 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, attendees will possess a solid understanding of MATLAB’s functionalities and will be equipped to address real-world data science challenges while streamlining their work via automation.

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

Course Format

• The course comprises both theoretical instruction and practical exercises, including case studies, sample code analysis, and hands-on implementation.

Note

• Practice sessions rely on pre-arranged sample data and report templates. If you have specific requirements, please contact us to make necessary arrangements.

This instructor-led live training in Malaysia (online or onsite) is designed for beginner-level developers and engineers seeking to learn how to apply numerical simulation to 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 integrates computation, visualization, and programming within an intuitive environment. It features the Financial Toolbox, which provides the necessary tools to conduct mathematical and statistical analysis on financial data, while presenting results through high-quality, presentation-ready graphics.

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

Upon completion of this training, participants will possess a comprehensive understanding of MATLAB’s Financial Toolbox features and will have acquired sufficient practical experience to immediately apply these skills to solve real-world financial challenges.

Audience

• Financial professionals who already have experience using MATLAB.

Course Format

• A blend 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 utilizing MATLAB for financial applications. Designed for beginners and those seeking a refresher, it assumes no prior programming experience or MATLAB knowledge. The curriculum explores key themes of 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
• Handling data files
• Working with data types
• Automating commands through scripts
• Writing programs with logic and flow control
• Creating functions
• Utilizing the Financial Toolbox for quantitative analysis

Object-Oriented Programming with MATLAB for Geophysics applies MATLAB’s OOP capabilities to develop structured, reusable, and maintainable code for geophysical data analysis and modelling.

This instructor-led live training (available online or onsite) targets 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:

• 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 modelling and analysis workflows.
• Enhance code reusability, scalability, and clarity for geoscience projects.

Format of the Course

• Interactive lecture and discussion.
• Ample 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.

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

Predictive analytics involves leveraging data analytics to forecast future outcomes. By combining data with techniques from data mining, statistics, and machine learning, this process establishes predictive models capable of anticipating future events.

In this instructor-led live training, participants will learn how to utilize Matlab to construct predictive models and apply them to large sample datasets to forecast future events based on the data.

Upon completing this training, participants will be able to:

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

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

This two-day course delivers a thorough introduction to the MATLAB® technical computing environment. Designed for beginner users and those seeking a refresher, the course assumes no prior programming experience or familiarity with MATLAB. Throughout the program, key themes such as data analysis, visualization, modeling, and programming are explored in depth.

The course is structured to teach the fundamentals of the Systems Modeling Language (SysML), its application via the MagicDraw/Cameo software, core Model-Based Systems Engineering (MBSE) simulation techniques, and industry best practices. This training also equips professionals with a background in architectural simulation, introduces the Simulation Toolkit plugin, covers the simulation of various diagram types, and demonstrates how to link diagram simulations to automate architectural processes.​

This course is designed for individuals seeking an alternative to the commercial MATLAB software. Over three days, participants will gain comprehensive knowledge on navigating the environment and utilizing the Octave package for data analysis and engineering calculations. The training caters to both beginners and those who already have some familiarity with the program and wish to systematize their understanding and enhance their skills. While prior knowledge of other programming languages is not mandatory, it can significantly ease the learning process. The course demonstrates practical applications through numerous real-world examples.

This instructor-led live training in Malaysia (online or onsite) is aimed at 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 used for modeling, simulating, and analyzing multidomain dynamic systems.