Basic MATLAB Programming Training Course

This four-day course provides a solid foundation in image processing using Matlab. You will learn how to modify and enhance images, as well as extract meaningful patterns from them. Additionally, you will gain the skills to build and apply 2D filters to images.

Throughout the analysis process, practical examples and hands-on exercises illustrate the effective use of relevant Matlab and Image Processing Toolbox functionalities.

This intensive three-day program offers a thorough introduction to the MATLAB technical computing environment. Designed for beginners as well as 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. The curriculum covers:

• Navigating the MATLAB user interface
• Inputting commands and establishing variables
• Analyzing vectors and matrices
• Visualizing data contained within vectors and matrices
• Managing data files
• Handling various data types
• Automating tasks through scripts
• Developing programs with logical structures 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 focuses on the core principles of MATLAB, highlighting its role as both a programming language and a comprehensive platform. Key topics include an introduction to MATLAB syntax, arrays and matrices, data visualization techniques, script development, and object-oriented programming concepts.

In the second segment, we illustrate how MATLAB can be leveraged for data mining, machine learning, and predictive analytics. To help participants clearly understand MATLAB’s capabilities and advantages, we compare its usage with other tools such as spreadsheets, C, C++, and Visual Basic.

The third segment teaches participants how to optimize their workflows by automating data processing and report generation tasks.

Throughout the course, participants will apply the concepts learned through hands-on exercises in a lab setting. By the conclusion of the training, participants will have a comprehensive understanding of MATLAB’s features and will be equipped to use it for solving real-world data science challenges and streamlining their work via automation.

Assessments will be integrated throughout the course to monitor progress.

Course Format

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

Note

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

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for beginner-level developers or engineers who wish to learn how to apply numerical simulation techniques 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 various approaches.

MATLAB seamlessly combines computation, visualization, and programming within an intuitive environment. It features the Financial Toolbox, providing essential capabilities for conducting mathematical and statistical analysis of financial data, along with the ability to present results through high-quality graphics.

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

Upon completing this training, participants will possess a comprehensive understanding of the powerful features within MATLAB's Financial Toolbox and will have acquired the practical skills necessary to immediately apply these tools to solve real-world financial challenges.

Audience

• Financial professionals who already have experience with MATLAB

Format of the course

• 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 applying MATLAB to financial applications. Designed for beginners and those seeking a refresher, no prior programming experience or MATLAB knowledge is required. Throughout the course, key themes such as data analysis, visualization, modeling, and programming are covered. Topics 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 using scripts
• Writing programs with logic and flow control
• Writing functions
• Utilizing the Financial Toolbox for quantitative analysis

Object-Oriented Programming with MATLAB for Geophysics refers to the use of MATLAB’s object-oriented programming (OOP) capabilities to develop structured, reusable, and maintainable code tailored 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 wish 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 core principles of object-oriented programming in MATLAB.
• Create and work with classes, properties, and methods for handling geophysical data.
• Apply OOP techniques to structure workflows for geophysical modeling and analysis.
• Improve code reusability, scalability, and clarity for geoscience projects.

Course Format

• Interactive lectures and group discussions.
• Abundant hands-on exercises and practice sessions.
• Live implementation in a real-time lab environment.

Course Customization Options

• To request a customized version of this course, please contact us to arrange the details.

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

Predictive analytics is the process of using data analytics to forecast future events. This approach combines data with data mining, statistics, and machine learning techniques to develop predictive models that anticipate upcoming outcomes.

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 forecast future events based on historical data.

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

• Build predictive models to identify patterns in historical and transactional data
• Apply predictive modeling to detect risks and uncover opportunities
• Construct mathematical models that capture key trends
• Leverage data from devices and business systems to minimize waste, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Course Format

• A blend of lectures, discussions, 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. No prior programming knowledge or experience with MATLAB is required. The course covers key themes such as data analysis, visualization, modeling, and programming.

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

This course is designed for individuals seeking an alternative to the commercial MATLAB package. 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 experienced users who wish to systematize their understanding and refine their skills. While prior knowledge of other programming languages is not a prerequisite, it significantly aids in learning. Throughout the course, practical examples will demonstrate how to effectively use the program.

This instructor-led, live training in Uzbekistan (online or on-site) is designed for Matlab users who wish to explore or transition to Python for data analytics and visualisation.

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

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

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