Introduction to Image Processing using Matlab Training Course

This three-day course provides a comprehensive overview of MATLAB’s primary interface, including its main screens and windows, covering:

• Using MATLAB as a calculator and plotting basic curves
• Creating custom functions and scripts

This three-day program offers a thorough introduction to the MATLAB technical computing environment. Designed for beginners or those seeking a refresher, it assumes no previous programming experience or familiarity with MATLAB. The course explores key themes of data analysis, visualization, modeling, and programming. Key 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
• Developing programs with logic and flow control
• Writing 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 explores the core principles of MATLAB, highlighting its role as both a programming language and a comprehensive platform. This section introduces essential topics including MATLAB syntax, arrays and matrices, data visualization techniques, script creation, and fundamental object-oriented concepts.

In the second segment, the course illustrates how MATLAB can be utilized for data mining, machine learning, and predictive analytics. To offer participants a clear and practical understanding of MATLAB's capabilities and advantages, we compare its usage with other tools such as spreadsheets, C, C++, and Visual Basic.

During the final segment, participants will learn how to enhance their efficiency by automating data processing workflows and report generation processes.

Throughout the course, participants will apply their knowledge through practical exercises in a laboratory setting. By the conclusion of the training, participants will possess a deep understanding of MATLAB's features, enabling them to tackle real-world data science challenges and automate tasks to improve workflow efficiency.

Progress assessments will be integrated throughout the course to evaluate participant development.

Course Format

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

Important Note

• Practice sessions will utilize pre-arranged sample data report templates. If you have specific customization needs, please contact us to make arrangements.

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

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

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

MATLAB seamlessly combines computation, visualization, and programming within an intuitive environment. It features the Financial Toolbox, which provides the essential tools for conducting mathematical and statistical analyses of financial data, alongside the capability to present results through high-quality graphics.

This instructor-led course offers a foundational introduction to using MATLAB in the context of finance. Through hands-on exercises and extensive in-lab practice, participants will explore data analysis, visualization, modeling, and programming techniques.

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

Audience

• Financial professionals who already have experience with MATLAB.

Course Format

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

This course offers a thorough introduction to the MATLAB technical computing environment, along with an overview of its application in finance. Designed for beginners and those seeking a refresher, it assumes no prior programming background or familiarity with MATLAB. 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 creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Managing data files
• Handling various data types
• Automating tasks via scripts
• Developing programs with logical structures and flow control
• Defining and using functions
• Leveraging the Financial Toolbox for quantitative analysis

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

This instructor-led live training, available both online and onsite, is designed for beginner-level MATLAB users in the field of geophysics who aim to learn how to design and implement object-oriented solutions for geophysical applications.

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

• Grasp the fundamentals of object-oriented programming within MATLAB.
• Create and utilize classes, properties, and methods for handling geophysical data.
• Apply OOP techniques to structure workflows for geophysical modeling 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 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. By combining data with techniques from data mining, statistics, and machine learning, this process establishes predictive models capable of anticipating upcoming events.

Through this instructor-led live training, attendees will learn to utilize Matlab for constructing predictive models and applying them to extensive datasets to predict future trends based on historical information.

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

• Develop predictive models to detect patterns within historical and transactional data
• Employ predictive modeling to pinpoint potential risks and opportunities
• Construct mathematical models that encapsulate significant trends
• Leverage data from devices and business systems to minimize waste, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Course Format

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

This two-day program offers a thorough introduction to the MATLAB® technical computing environment. It is designed for beginners and those seeking a refresher. No previous programming background or familiarity with MATLAB is expected. The course covers essential themes including data analysis, visualization, modeling, and programming.

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

This course is designed for individuals seeking an open-source alternative to the commercial MATLAB software. Over the course of three days, participants will gain comprehensive insights into navigating the Octave environment and utilizing the Octave package for data analysis and engineering computations. The curriculum is tailored for both beginners and those who already have some familiarity with the program and wish to structure their understanding and enhance their proficiency. While prior knowledge of other programming languages is not a prerequisite, it can significantly accelerate the learning process. Through numerous practical examples, the course demonstrates how to effectively apply the software in real-world scenarios.

This instructor-led, live training in Turkey (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.