Introduction to Image Processing using Matlab Training Course

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

• utilizing MATLAB as a calculator and plotting basic curves
• developing custom functions and scripts

This three-day program delivers 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 knowledge of MATLAB. Throughout the training, participants will explore key themes such as 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
• Working with various data types
• Automating commands through 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

The initial segment of this training establishes a solid foundation in MATLAB, exploring its dual role as both a programming language and a computational platform. Key topics include MATLAB syntax, arrays and matrices, data visualization techniques, script development, and the core principles of object-oriented programming.

In the second segment, the course demonstrates MATLAB's capabilities in data mining, machine learning, and predictive analytics. To illustrate MATLAB's unique advantages and power, we draw comparisons between using MATLAB and other common tools such as spreadsheets, C, C++, and Visual Basic.

The final segment focuses on streamlining workflows by automating data processing and report generation tasks.

Throughout the course, participants will reinforce their learning through hands-on exercises within a lab environment. By the conclusion of the training, participants will possess a comprehensive understanding of MATLAB's capabilities, enabling them to solve real-world data science problems and automate routine tasks for greater efficiency.

Progress will be evaluated through assessments conducted throughout the course.

Course Format

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

Note

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

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

Upon completing this training, participants will be able to:

• Grasp the fundamentals of dynamic analysis.
• Utilize Matlab to perform analytical and numerical solutions.
• Derive motion equations using various approaches.

MATLAB seamlessly integrates computation, visualization, and programming within a user-friendly environment. It includes the Financial Toolbox, offering essential features for conducting mathematical and statistical analyses of financial data, while displaying results with presentation-quality graphics.

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

Upon completing this training, participants will possess a thorough understanding of the powerful features in MATLAB's Financial Toolbox and will have gained sufficient practice to immediately apply them to solve real-world problems.

Audience

• Financial professionals with prior experience using MATLAB

Course Format

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

This course offers a thorough introduction to the MATLAB technical computing environment, along with guidance on leveraging MATLAB for financial applications. Designed for beginners and those seeking a refresher, no prior programming experience or familiarity with MATLAB is required. Throughout the course, key themes such as data analysis, visualization, modeling, and programming are explored. 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 using scripts
• Developing programs with logic and flow control
• Creating functions
• Utilizing the Financial Toolbox for quantitative analysis

Applying MATLAB's OOP capabilities to build structured, reusable, and maintainable code for geophysical data analysis and modeling.

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

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

Predictive analytics involves leveraging data analytics to forecast future outcomes. This approach utilizes data, combined with data mining, statistical analysis, and machine learning techniques, to construct predictive models for anticipating 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 datasets 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 two-day course offers a comprehensive introduction to the MATLAB® technical computing environment. It is designed for beginner users and those seeking a refresher. No prior programming experience or knowledge of MATLAB is required. The course explores key themes of data analysis, visualization, modeling, and programming throughout.

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. The training also equips professionals with an understanding of architectural simulation, introduces the Simulation Toolkit plugin, covers the simulation of various diagram types, and demonstrates how to integrate diagram simulations to automate the architecture.​

This course is designed for individuals seeking an alternative to the commercial MATLAB package. Over three days, the training offers comprehensive guidance on navigating the Octave environment and utilizing it for data analysis and engineering calculations. It caters to both beginners and experienced users who wish to systematize their knowledge and refine their skills. While prior programming experience is not mandatory, familiarity with other languages will significantly accelerate the learning process. Through numerous practical examples, participants will learn how to effectively leverage Octave in real-world scenarios.

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