Dynamic Analysis Using Matlab Training Course

A 3-day course designed to guide you through the main screens and windows of MATLAB, covering ...

• using MATLAB as a calculator and plotting basic curves
• creating your own customised functions and scripts

This four-day course offers a foundational understanding of image processing using Matlab. During the course, you 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 analysis process, examples and exercises will illustrate the effective use of Matlab and its 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, the course assumes no prior programming experience or knowledge of MATLAB. The curriculum covers key themes such as data analysis, visualization, modeling, and programming. The topics 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 that incorporate logic and flow control
• Developing functions

In this instructor-led, live training, participants will learn how to use Matlab to design, construct, 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 services, or clusters

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

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

During the second phase, 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 segment of the training, participants will learn how to enhance their efficiency by automating data processing and report generation tasks.

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 deep understanding of MATLAB's features and will be able to use it effectively for solving real-world data science problems and streamlining their workflows through automation.

Assessments will be conducted throughout the course to monitor progress.

Format of the Course

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

Note

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

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

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

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 with the practical skills needed to apply these tools effectively to real-world problems.

Audience

• Financial professionals who have prior experience with MATLAB

Format of the course

• Part lecture, part discussion, with a strong emphasis on 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. It is 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 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 with scripts
• Writing programs using logic and flow control
• Creating functions
• Leveraging the Financial Toolbox for quantitative analysis

Object-Oriented Programming with MATLAB for Geophysics involves utilizing MATLAB’s object-oriented programming features 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 are interested in learning how to design and implement object-oriented solutions 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.
• Apply OOP techniques to structure geophysical modeling and analysis workflows effectively.
• Improve code reusability, scalability, and clarity for geoscience projects.

Format of the Course

• Interactive lecture and discussion sessions.
• Extensive exercises and practice opportunities.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

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

Predictive analytics involves using data analytics to forecast future events. This approach combines data with data mining, statistical methods, and machine learning to develop models that can predict future outcomes.

In this instructor-led, live training, participants will learn how to use Matlab to create predictive models and apply them to large datasets to anticipate future events 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
• Use predictive modeling techniques to recognize risks and opportunities
• Develop mathematical models that capture significant trends
• Leverage data from devices and business systems to optimize processes, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, with practical 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 requires no prior programming experience or knowledge of MATLAB. Throughout the sessions, participants will explore key themes such as data analysis, visualization, modeling, and programming.

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 who are interested in exploring an alternative program to the commercial MATLAB package. Over the course of three days, participants will gain a thorough understanding of navigating the OCTAVE environment and performing data analysis and engineering calculations. The training is suitable for beginners as well as 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 the learning process. The course will provide numerous practical examples to demonstrate how to effectively use the program.

This instructor-led, live training in Serbia (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 environment used for modeling, simulating, and analyzing complex dynamic systems across multiple domains.