Introduction to Image Processing using Matlab Training Course

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

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

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.

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 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.

This course provides comprehensive material on MATLAB as a potent simulation tool for communications. The primary objective is to introduce MATLAB not merely as a general programming language, but to emphasize the critical role of its powerful capabilities in simulation. The examples provided to illustrate the course material go beyond direct command usage; they often address real-world problems.