Basic MATLAB Programming Training Course

This four-day course offers foundational knowledge in image processing using Matlab. Participants will practice techniques for modifying and enhancing images, as well as extracting patterns from them. Additionally, you will learn how to construct 2D filters and apply them to images.

Throughout the course, examples and exercises illustrate the effective use of Matlab and its Image Processing Toolbox, guiding you through the entire analysis process.

This three-day course offers a thorough introduction to the MATLAB technical computing environment. Designed for beginners and those seeking a refresher, no prior programming experience or familiarity with MATLAB is required. The course delves into themes of data analysis, visualization, modeling, and programming. Key topics include:

• Navigating the MATLAB user interface
• Executing commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Managing data files
• Working with various data types
• Automating tasks using scripts
• Writing programs that incorporate logic and flow control
• Developing functions

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

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

• Create a deep learning model
• Automate data labeling processes
• Work with models from Caffe and TensorFlow-Keras
• Train data using multiple GPUs, cloud services, or clusters

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

In the initial segment of this training, we delve into the foundational aspects of MATLAB, exploring its role as both a programming language and an integrated platform. This section covers an introduction to MATLAB's syntax, arrays and matrices, data visualization techniques, script creation, and object-oriented programming principles.

During the second part, we showcase how MATLAB can be utilized for data mining, machine learning, and predictive analytics. To provide participants with a clear and practical understanding of MATLAB's capabilities, we compare its use to other tools such as spreadsheets, C, C++, and Visual Basic.

In the third segment, participants will learn techniques to streamline their work by automating data processing and report generation tasks.

Throughout the training, participants will apply the concepts learned through hands-on exercises in a laboratory setting. By the end of the course, participants will have a comprehensive understanding of MATLAB's features and will be able to use it effectively for solving real-world data science problems as well as automating their workflows.

Assessments will be conducted throughout the training to monitor progress.

Format of the Course

• The course combines theoretical discussions with practical exercises, including case studies, code reviews, and hands-on implementation.

Note

• Practice sessions will use pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange them.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at 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 combines computation, visualization, and programming in a user-friendly environment. It provides the Financial Toolbox, which includes essential features for performing mathematical and statistical analysis of financial data, followed by presenting the results with high-quality graphics.

This instructor-led training offers an introduction to MATLAB for finance. Participants will delve into data analysis, visualization, modeling, and programming through hands-on exercises and extensive in-lab practice.

By the end of this training, participants will have a comprehensive understanding of the powerful features included in MATLAB's Financial Toolbox and will be equipped to apply them immediately to solve real-world problems.

Audience

• Financial professionals with prior experience using MATLAB

Format of the course

• A blend of lecture, discussion, and intensive hands-on practice

This course offers a thorough introduction to the MATLAB technical computing environment, along with an overview of using MATLAB for financial applications. Designed for beginners and those seeking a refresher, the course assumes no prior programming experience or knowledge of MATLAB. Key themes such as data analysis, visualization, modeling, and programming are explored throughout the course. The topics covered include:

• Navigating the MATLAB user interface
• Inputting commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Handling data files
• Working with various data types
• Automating tasks with scripts
• Writing programs that include logic and flow control
• Creating functions
• Leveraging the Financial Toolbox for quantitative analysis

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

Predictive analytics involves using data analysis to forecast future outcomes. This process combines data with techniques such as data mining, statistics, and machine learning to develop a model that can predict future events.

In this instructor-led, live training, participants will learn how to use Matlab to create predictive models and apply them to large datasets to anticipate future events based on the available data.

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

• Create predictive models to identify patterns in historical and transactional data
• Use predictive modeling to recognize potential risks and opportunities
• Develop mathematical models that capture significant trends
• Leverage data from devices and business systems to optimize processes, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, with exercises and extensive hands-on practice

This two-day course offers a thorough introduction to the MATLAB® technical computing environment. Designed for beginners and those seeking a refresher, the course assumes no prior programming experience or familiarity with MATLAB. Throughout the course, participants will explore key themes such as data analysis, visualization, modeling, and programming.

This course is designed for individuals interested in exploring an alternative to the commercial MATLAB package. Over three days, the training offers a thorough introduction to navigating and utilizing the OCTAVE package for data analysis and engineering calculations. The course caters to both beginners and those with prior experience who wish to systematize their knowledge and enhance their skills. While familiarity with other programming languages is not necessary, it can significantly aid in learning. The course will provide practical examples to demonstrate how to effectively use the program.

This instructor-led, live training in Uzbekistan (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 is a visual programming environment used for modeling, simulating, and analyzing complex dynamic systems across multiple domains.

This course provides extensive material on MATLAB, highlighting its strength as a simulation tool for communications. The primary goal of this course is to introduce MATLAB not merely as a general programming language but to emphasize its powerful capabilities as a simulation tool. The examples used throughout the course are not just simple applications of MATLAB commands; instead, they often address real-world problems.

Objective: This training is designed for software engineers working with Model-Based Design (MBD) technology. It will cover modeling techniques for automotive systems, automotive industry standards, auto-code generation, and the construction and verification of model test harnesses. Audience: Software developers for automotive suppliers.