Dynamic Analysis Using Matlab Training Course

A 3-day course that guides you through the main screens and windows of MATLAB, including...

• how to use MATLAB as a calculator and plot basic curves
• how to create your own customised functions and scripts

This four-day course offers a comprehensive introduction to 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 course, examples and exercises will illustrate the effective use of Matlab and its Image Processing Toolbox, guiding you through the entire analysis process.

This three-day course offers a thorough introduction to the MATLAB technical computing environment. Designed for beginners and those seeking a refresher, no prior programming experience or knowledge of MATLAB is required. The course covers key themes such as data analysis, visualization, modeling, and programming. Topics include:

• Navigating the MATLAB user interface
• Executing commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Managing data files
• Working with various data types
• Automating tasks with scripts
• Writing programs using logic and flow control
• Developing 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:

• Create a deep learning model
• Automate data labeling processes
• Work with models from Caffe and TensorFlow-Keras
• Train data using multiple GPUs, cloud resources, or clusters

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

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

In the second segment, 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 to other tools such as spreadsheets, C, C++, and Visual Basic.

The third part of the training focuses on enhancing efficiency by automating data processing and report generation processes.

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 solid understanding of MATLAB's functionalities and will be equipped to use it for solving real-world data science problems and streamlining their work through automation.

Regular assessments will be conducted throughout the course to monitor progress.

Format of the Course

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

Note

• Practice sessions will use pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange for customized content.

MATLAB combines computation, visualization, and programming in a user-friendly environment. It features the Financial Toolbox, which equips users with the tools needed to perform mathematical and statistical analysis of financial data, and then present the results using high-quality graphics.

This instructor-led training offers an introduction to MATLAB for finance. 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 included in MATLAB's Financial Toolbox and will be well-prepared to apply them immediately to solve real-world problems.

Audience

• Financial professionals with prior experience using 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. 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
• Executing 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 that incorporate logic and flow control
• Creating functions
• Utilizing the Financial Toolbox for quantitative analysis

Object-Oriented Programming with MATLAB for Geophysics involves applying MATLAB’s object-oriented programming (OOP) features to develop structured, reusable, and maintainable code for geophysical data analysis and modeling.

This instructor-led, live training (available online or onsite) is designed for beginner-level MATLAB users in the field of geophysics who wish to learn how to design and implement object-oriented solutions tailored for geophysical applications.

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

• Grasp the fundamentals of object-oriented programming in MATLAB.
• Create and manage classes, properties, and methods for handling geophysical data.
• Utilize OOP techniques to structure geophysical modeling and analysis workflows effectively.
• Improve code reusability, scalability, and clarity for geoscience projects.

Format of the Course

• Interactive lectures and discussions.
• Plenty of exercises and practice sessions.
• 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 created by MathWorks.

Predictive analytics involves using data analysis to forecast future outcomes. This approach leverages data in conjunction with data mining, statistical methods, and machine learning to develop predictive models that can anticipate future events.

In this instructor-led, live training, participants will learn how to use Matlab to construct predictive models and apply them to large datasets to predict future scenarios 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
• Utilize predictive modeling to recognize risks and opportunities
• Develop mathematical models that capture significant trends
• Leverage data from devices and business systems to minimize waste, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, with 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 familiarity with MATLAB. Key themes such as data analysis, visualization, modeling, and programming are explored in depth throughout the course.

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 to the commercial MATLAB package. Over the course of three days, participants will gain a thorough understanding of navigating and utilizing the OCTAVE package for data analysis and engineering calculations. The training is suitable for both beginners and those with existing knowledge of the program who wish to organize their skills and enhance their proficiency. While familiarity with other programming languages is not necessary, it can significantly aid in learning. The course will provide numerous practical examples to illustrate how to effectively use the program.

This instructor-led, live training in Norway (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 graphical programming environment designed for the modeling, simulation, and analysis of multidomain dynamic systems.