Dynamic Analysis Using Matlab Training Course

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

• how to use matlab as a caluclator and plot basic curves
• how to create your own customized functions and scripts

This four-day course delivers foundational knowledge in image processing utilizing MATLAB. Participants will gain hands-on experience modifying and enhancing images, as well as extracting patterns from them. Additionally, the curriculum covers the construction of two-dimensional filters and their application to images.

Practical examples and exercises illustrate the effective use of relevant MATLAB and Image Processing Toolbox functionalities throughout the analysis workflow.

This three-day program 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. Throughout the course, key themes such as data analysis, visualization, modeling, and programming are explored. 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
• Managing data types
• Automating commands via 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

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

In the second section, 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 power, we draw comparisons between using MATLAB and other tools such as spreadsheets, C, C++, and Visual Basic.

In the final section, participants learn how to streamline their workflow by automating data processing and report generation.

Throughout the course, participants will apply learned concepts through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough grasp of MATLAB's capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation.

Assessments will be conducted throughout the course to gauge progress.

Format of the Course

• The course includes theoretical and practical exercises, featuring case discussions, sample code inspection, and hands-on implementation.

Note

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

MATLAB seamlessly integrates computation, visualization, and programming within an intuitive environment. It features the Financial Toolbox, which provides the essential tools for conducting mathematical and statistical analysis of financial data, alongside presentation-quality graphics for displaying results.

This instructor-led training serves as an introduction to using MATLAB in the financial sector. Participants will explore data analysis, visualization, modeling, and programming through hands-on exercises and extensive in-lab practice.

Upon completing this training, participants will possess a comprehensive understanding of the powerful features within MATLAB's Financial Toolbox. They will also have gained sufficient practical experience to immediately apply these skills to solve real-world problems.

Audience

• Financial professionals who already have experience with MATLAB

Course Format

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

This course offers a comprehensive 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, it assumes no prior programming experience or MATLAB knowledge. Key themes throughout the course include data analysis, visualization, modeling, and programming. Topics covered include:

• Navigating the MATLAB user interface
• Entering commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Managing data files
• Working with various data types
• Automating commands via scripts
• Writing programs with logic and flow control
• Writing functions
• Utilizing the Financial Toolbox for quantitative analysis

Object-Oriented Programming with MATLAB for Geophysics involves leveraging MATLAB’s OOP capabilities to develop structured, reusable, and maintainable code tailored for geophysical data analysis and modeling.

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

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

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

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• 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 leveraging data analytics to forecast future outcomes. This methodology combines data with techniques from data mining, statistics, and machine learning to construct predictive models capable of anticipating upcoming events.

In this instructor-led live training, participants will learn to utilize Matlab for constructing 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 within historical and transactional data
• Employ 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, conserve time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Course Format

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

This two-day program 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. Throughout the course, key themes such as data analysis, visualization, modeling, and programming are thoroughly explored.

The course is structured to teach the core principles of the Systems Modeling Language (SysML), its implementation via MagicDraw/Cameo software, fundamental MBSE simulation techniques, and industry best practices. This training also equips professionals with insights into architectural simulation, introduces the Simulation Toolkit plugin, covers the simulation of various diagram types, and demonstrates how to link diagram simulations to automate architecture workflows.​

This course is designed for individuals seeking a powerful alternative to the commercial MATLAB suite. Over three days, participants will gain comprehensive insights into navigating the environment and utilizing the Octave package for data analysis and engineering computations. The training caters to both beginners and those with prior experience who wish to systematize their understanding and refine their skills. While knowledge of other programming languages is not mandatory, it significantly accelerates the learning process. Through numerous practical examples, the course demonstrates how to effectively apply the program in real-world scenarios.

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 provides a graphical programming environment designed for modeling, simulating, and analyzing multidomain dynamic systems.