Basic MATLAB Programming Training Course

This four-day course establishes 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 expertise in designing two-dimensional filters and applying them to image data.

Throughout the analysis process, practical examples and exercises illustrate the effective use of relevant MATLAB and Image Processing Toolbox functions.

This three-day course delivers 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. The curriculum covers the following topics:

• Navigating the MATLAB user interface
• Inputting commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Handling data files
• Managing data types
• Automating commands via scripts
• Developing programs with logic and flow control
• Writing functions

In this instructor-led, live training, participants will learn how to utilize Matlab to design, construct, and visualize a convolutional neural network for image recognition.

Upon completing this training, participants will be capable of:

• Constructing a deep learning model
• Automating the data labeling process
• Utilizing models from Caffe and TensorFlow-Keras
• Training data across multiple GPUs, cloud environments, or clusters

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

The initial segment of this training establishes the core concepts of MATLAB, exploring its dual role as both a programming language and a comprehensive platform. This section introduces essential MATLAB syntax, array and matrix operations, data visualization techniques, script development methodologies, and the principles of object-oriented programming.

During the second phase, we illustrate how MATLAB can be leveraged for data mining, machine learning, and predictive analytics. To highlight MATLAB’s unique advantages and power, we compare its functionality against other common tools such as spreadsheets, C, C++, and Visual Basic, offering participants a practical and clear perspective.

In the final segment, attendees learn strategies to streamline their workflow by automating data processing and report generation tasks.

Throughout the course, participants will apply theoretical knowledge through practical exercises in a dedicated lab environment. Upon completion, participants will possess a robust understanding of MATLAB’s capabilities, enabling them to solve real-world data science challenges and automate their professional tasks effectively.

Progress will be monitored through continuous assessments conducted throughout the course.

Course Format

• The course combines theoretical instruction with practical exercises, including case study discussions, code analysis, and hands-on implementation.

Note

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

This instructor-led, live training in Greece (online or on-site) is designed for beginner-level developers or engineers who wish to learn how to use numerical simulation for 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 different approaches.

MATLAB seamlessly combines computation, visualization, and programming within an intuitive environment. It features the Financial Toolbox, providing the essential tools for conducting mathematical and statistical analysis on financial data, alongside the capability to present findings with high-quality graphics.

This instructor-led training serves as a comprehensive introduction to using MATLAB in the financial sector. Through extensive hands-on exercises and ample lab practice, participants will delve into data analysis, visualization, modeling, and programming.

Upon completion, attendees will possess a deep understanding of the powerful features within MATLAB's Financial Toolbox and will have acquired the practical skills necessary to immediately apply them to real-world financial challenges.

Audience

• Financial professionals who already have experience with MATLAB

Course Format

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

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

• Navigating the MATLAB user interface
• Inputting commands and defining variables
• Performing analysis on vectors and matrices
• Visualizing data from vectors and matrices
• Managing data files
• Handling various data types
• Automating tasks via scripts
• Developing programs with logical flow and control structures
• 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 maintainable code for the analysis and modelling of geophysical data.

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 for geophysical applications.

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

• Grasp the fundamentals of object-oriented programming within MATLAB.
• Create and utilise classes, properties, and methods for managing geophysical data.
• Apply OOP techniques to structure workflows for geophysical modelling and analysis.
• 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.

Course Customization Options

• To request 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 insights to forecast future outcomes. This methodology combines data mining, statistical analysis, and machine learning techniques to construct predictive models capable of anticipating upcoming events.

During this instructor-led live training, participants will acquire the skills necessary to utilize Matlab for constructing predictive models and applying them to extensive datasets to forecast future trends based on historical data.

Upon completing this training, participants will be able to:

• Develop predictive models to analyze patterns within historical and transactional data
• Employ predictive modeling to uncover potential risks and business opportunities
• Construct mathematical models that accurately reflect significant trends
• Utilize data from IoT devices and enterprise systems to minimize waste, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

Over the course of two days, this program delivers a thorough introduction to the MATLAB® technical computing environment. Designed for beginners and those seeking a refresher, no previous programming background or familiarity with MATLAB is required. The curriculum covers essential themes such as data analysis, visualization, modeling, and programming.

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

This course is designed for individuals seeking a commercial alternative to the MATLAB package. Over three days, participants will gain comprehensive insights into navigating the environment and utilizing Octave for data analysis and engineering calculations. The training caters to both beginners and experienced users aiming to systematize their knowledge and refine their skills. While prior experience with other programming languages is not mandatory, it can significantly accelerate the learning process. Through numerous practical examples, the course demonstrates effective usage of the software.

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