Dynamic Analysis Using Matlab Training Course

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

• leveraging MATLAB as a calculator and visualizing fundamental graphs
• developing custom functions and scripts

This four-day course provides image processing foundations using Matlab. You will learn how to modify and enhance images, as well as extract patterns from them. You will also gain insights on constructing 2D filters and applying them to images.

Examples and exercises demonstrate the use of appropriate Matlab and Image Processing Toolbox functionality throughout the analysis process.

This three-day program offers a thorough introduction to the MATLAB technical computing environment. It is designed for beginners and those seeking a refresher. No prior programming background or MATLAB knowledge is required. The course covers key themes such as data analysis, visualization, modeling, and programming. Topics 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
• Writing programs with 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:

• 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 covers the core principles of MATLAB, highlighting its dual role as both a programming language and a comprehensive platform. This section introduces MATLAB syntax, arrays and matrices, data visualization techniques, script development, and the fundamentals of object-oriented programming.

In the second segment, we demonstrate how to leverage MATLAB for data mining, machine learning, and predictive analytics. To give participants a clear and practical understanding of MATLAB's capabilities and efficiency, we compare its approach with other tools such as spreadsheets, C, C++, and Visual Basic.

During the third segment, participants will learn how to optimize their workflows by automating data processing and report generation.

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

Progress assessments will be conducted throughout the course to monitor advancement.

Course Format

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

Note

• Practice sessions utilize pre-arranged sample data report templates. For specific requirements, please contact us to arrange customization.

MATLAB brings computation, visualization, and programming together in a user-friendly environment. It includes the Financial Toolbox, which provides the essential tools for conducting mathematical and statistical analyses on financial data, and for presenting the results through high-quality graphics.

This instructor-led training introduces participants to MATLAB in the context of finance. Through hands-on exercises and ample in-lab practice, the course covers data analysis, visualization, modeling, and programming.

Upon completion, participants will have a comprehensive understanding of the powerful features within MATLAB's Financial Toolbox and will have gained sufficient practical experience to apply them immediately to real-world challenges.

Audience

• Financial professionals who already have experience with MATLAB

Course Format

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

This course offers a thorough introduction to the MATLAB technical computing environment, along with a foundational guide to applying MATLAB in financial contexts. Designed for beginners and those seeking a refresher, no prior programming background or MATLAB knowledge is required. The curriculum explores key themes such as data analysis, visualization, modeling, and programming. Key topics covered include:

• Navigating the MATLAB user interface
• Entering commands and defining variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Managing data files
• Handling various data types
• Automating tasks via scripts
• Developing programs with logic and flow control
• Creating functions
• Leveraging the Financial Toolbox for quantitative analysis

Object-Oriented Programming with MATLAB for Geophysics involves applying MATLAB’s OOP capabilities to develop structured, reusable, and easily 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 geophysics field 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.
• Lots of 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 combines data with techniques from data mining, statistics, and machine learning to construct predictive models that anticipate upcoming events.

In this instructor-led live training, participants will acquire the skills to use Matlab for building predictive models and applying them to large-scale datasets to predict future occurrences based on historical data.

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

• Develop predictive models to analyze patterns in historical and transactional data
• Utilize predictive modeling to identify potential risks and opportunities
• Construct 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

• Combination 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, it assumes no prior programming experience or familiarity with MATLAB. The curriculum explores key themes including data analysis, visualization, modeling, and programming.

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

This course is designed for individuals seeking a free and open-source alternative to the commercial MATLAB software. Over the course of three days, participants will gain a thorough understanding of navigating the Octave environment and utilizing the Octave package for data analysis and engineering computations. The training is suitable for both beginners and those with prior experience who wish to structure their existing knowledge and enhance their proficiency. While familiarity with other programming languages is not a prerequisite, it can significantly aid the learning process. Through numerous practical examples, the course demonstrates effective ways to leverage the program.

This instructor-led, live training in Norway (online or onsite) is aimed at Matlab users who wish to explore 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 provides a graphical programming environment designed for modeling, simulating, and analyzing multidomain dynamic systems.