Introduction to Image Processing using Matlab Training Course

Establishing core competencies in MATLAB programming opens the door to a flexible platform for technical computing and numerical analysis. This course explores essential concepts including variable handling, array operations, matrix algebra, control structures, the creation of custom functions, and script development. Participants will navigate practical workflows such as data visualization, plotting techniques, and algorithm development, which are critical for engineering simulations and mathematical modeling projects.

This three-day course offers a comprehensive introduction to the MATLAB technical computing environment. Designed for beginners and those seeking a refresher, it assumes no prior programming experience or knowledge of MATLAB. The curriculum explores key themes of data analysis, visualization, modeling, and programming, covering topics such as:

• Navigating the MATLAB user interface
• Entering commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Working with data files
• Managing data types
• Automating commands through scripts
• Writing programs with logic and flow control
• Creating functions

In this instructor-led, live training, participants will acquire the skills to design, build, and visualize a convolutional neural network for image recognition using Matlab.

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

• Construct deep learning models
• Automate the data labeling process
• Utilize models from Caffe and TensorFlow-Keras
• Train data using multiple GPUs, cloud services, or clusters

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

This instructor-led live training in Kenya (online or onsite) is designed for beginner-level developers or engineers who wish to learn how to apply numerical simulation for dynamic problems using Matlab.

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

• Grasp the fundamentals of dynamic analysis.
• Utilize Matlab to conduct analytical and numerical solutions.
• Derive motion equations through various approaches.

MATLAB brings together computation, visualization, and programming within a user-friendly environment. It features the Financial Toolbox, which provides the essential tools for conducting mathematical and statistical analysis of financial data, and for presenting the findings through high-quality graphics.

This instructor-led course offers an introduction to using MATLAB for finance. Through hands-on exercises and extensive in-lab practice, participants will explore data analysis, visualization, modeling, and programming.

Upon completion of this training, participants will have a comprehensive understanding of the powerful capabilities within MATLAB's Financial Toolbox and will have gained the practical experience needed to immediately apply these skills to solve real-world problems.

Audience

• Financial professionals who already have experience with MATLAB

Format of the course

• A mix of lectures, discussions, 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 geophysical data analysis and modelling.

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:

• 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.
• Extensive 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.

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. Key themes such as data analysis, visualization, modeling, and programming are explored throughout the sessions.

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

This instructor-led, live training in Kenya (online or onsite) is designed for Matlab users who wish to explore or transition to Python for data analytics and visualization.

Upon completing this training, participants will be able to:

• Install and set up a Python development environment.
• Comprehend the differences and similarities between Matlab and Python syntax.
• Utilise Python to extract insights from diverse datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

Elevate your automotive engineering skills with this advanced Simulink training course, which integrates theoretical models of multidomain dynamic systems with practical applications using Simulink/Stateflow verifiers, Reactis tools, and Matelo applications. Tailored for automotive systems engineers, control specialists, and MATLAB/Simulink professionals aiming to master complex automotive modeling, this course provides hands-on expertise in solver selection, subsystem simulation parameters, and system verification. Participants will learn to build reliable, high-performance automotive control models and accelerate vehicle development cycles.

This course provides comprehensive materials on using MATLAB as a robust simulation tool for communications. The primary goal is to present MATLAB not merely as a general-purpose programming language, but to highlight its exceptional capabilities as a simulation environment. The examples used to illustrate the course material go beyond simple command execution; they often address real-world engineering problems.

Purpose: This course is designed for Software Engineers specializing in Model-Based Design (MBD) technology. The curriculum covers automotive system modeling techniques, industry standards, automated code generation, and the creation and verification of model test harnesses. Target Audience: Software Developers employed by automotive suppliers.