Basic MATLAB Programming Training Course

This four-day course establishes the foundational principles of image processing using MATLAB. Participants will gain hands-on experience in modifying and enhancing images, as well as extracting patterns from them. The curriculum also covers the construction of 2D filters and their application to image data.

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

This three-day program offers a comprehensive 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. Key themes of data analysis, visualization, modeling, and programming are woven throughout the curriculum. 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
• Managing data types
• Automating commands through scripts
• Developing programs with logic and flow control
• Writing functions

During 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

In the initial phase of this training, we explore the core fundamentals of MATLAB, highlighting its role as both a programming language and a comprehensive platform. This section introduces MATLAB syntax, arrays and matrices, data visualization techniques, script development, and object-oriented principles.

The second phase demonstrates the application of MATLAB in data mining, machine learning, and predictive analytics. To offer participants a clear and practical understanding of MATLAB's capabilities and advantages, we draw comparisons between utilizing MATLAB and other tools such as spreadsheets, C, C++, and Visual Basic.

In the final phase, participants learn how to optimize their workflow by automating data processing and report generation tasks.

Throughout the course, participants will apply the concepts learned through practical exercises in a lab environment. By the end of the training, participants will have a comprehensive understanding of MATLAB's capabilities and will be able to leverage it to solve real-world data science problems and streamline their work through automation.

Assessments will be conducted throughout the course to monitor progress.

Course Format

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

Note

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

This instructor-led live training, accessible online or onsite, is tailored for beginner-level developers and engineers seeking to master numerical simulation for dynamic problems using Matlab.

By the conclusion 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 within an intuitive environment. It features the Financial Toolbox, which provides essential tools for conducting mathematical and statistical analysis of financial data, alongside the capability to present results through high-quality graphics.

This instructor-led training introduces participants to the application of MATLAB in the financial sector. The curriculum covers data analysis, visualization, modeling, and programming through extensive hands-on exercises and in-lab practice sessions.

Upon completion of this training, participants will possess a comprehensive understanding of the robust features available in MATLAB's Financial Toolbox. They will also have acquired the practical skills necessary to immediately apply these tools to resolve real-world financial challenges.

Audience

• Financial professionals who already have experience using MATLAB

Course Format

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

This course offers a thorough introduction to the MATLAB technical computing environment, along with an overview of applying MATLAB to financial scenarios. It is designed for beginners and professionals seeking a refresher, requiring no prior programming background or familiarity with MATLAB. The curriculum explores key themes such as data analysis, visualization, modeling, and programming. Key topics covered include:

• Navigating the MATLAB user interface
• Inputting commands and defining variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Managing data files
• Working with different data types
• Automating workflows using scripts
• Developing programs with logic and flow control
• Writing custom functions
• Utilizing the Financial Toolbox for quantitative analysis

This course explores the application of MATLAB's Object-Oriented Programming (OOP) capabilities to develop structured, reusable, and maintainable code tailored for geophysical data analysis and modeling.

Delivered as an instructor-led live session (available online or onsite), this training is designed for beginner-level MATLAB users in the geophysics sector who aim to master the design and implementation of OOP solutions for geophysical applications.

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

• Grasp the core principles of object-oriented programming within MATLAB.
• Design and utilize classes, properties, and methods specifically for handling geophysical data.
• Implement OOP techniques to structure workflows for geophysical modeling and analysis.
• Improve code reusability, scalability, and clarity across geoscience projects.

Course Delivery Format

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

Customization Options

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

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

Predictive analytics involves utilizing data analytics to forecast future outcomes. This approach leverages data mining, statistical analysis, and machine learning methodologies to construct predictive models capable of forecasting subsequent events.

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

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

• Develop predictive models to analyze patterns within historical and transactional data
• Employ predictive modeling techniques to identify potential risks and opportunities
• Construct mathematical models that encapsulate significant trends
• Leverage data from devices and business systems to minimize waste, conserve time, and reduce expenses

Audience

• Developers
• Engineers
• Domain experts

Course Format

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

This intensive two-day program offers a thorough introduction to the MATLAB® technical computing environment. Designed for beginners and those seeking a refresher, the course assumes no prior programming background or familiarity with MATLAB. Participants will explore key themes including data analysis, visualization, modeling, and programming throughout the session.

This course is structured to teach the core principles of the Systems Modeling Language (SysML), its practical application using MagicDraw/Cameo software, fundamental MBSE simulation techniques, and industry best practices. The training also equips professionals with knowledge on architectural simulation foundations, introduces the Simulation Toolkit plugin, covers the simulation of various diagram types, and demonstrates how to integrate diagram simulations to automate architectural processes.​

This course is designed for individuals seeking an alternative to the commercial MATLAB software. The three-day program offers comprehensive guidance on navigating the environment and utilizing the OCTAVE package for data analysis and engineering calculations. It caters to both beginners and those already familiar with the tool who wish to systematize their knowledge and refine their skills. While prior experience with other programming languages is not mandatory, it significantly aids in the learning process. Through numerous practical examples, the course demonstrates effective ways to apply the software.

This instructor-led live training in the UAE (online or onsite) is designed for Matlab users seeking to explore or transition to Python for data analytics and visualization.

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

• Install and configure a Python development environment.
• Identify the differences and similarities between Matlab and Python syntax.
• Leverage Python to extract insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

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