Online nebo na místě, živé kurzy MATLABu vedené instruktorem demonstrují prostřednictvím praktické praxe základy programování MATLABu (syntaxe, pole a matice, vizualizace dat, vývoj skriptů, objektově orientované principy atd.) a také to, jak aplikovat MATLAB. balíčky jako Financial Toolbox pro provádění matematických a statistických analýz finančních dat. Kurzy MATLABu také zahrnují, jak používat související technologie, jako je Simulink, k modelování složitých systémů. Školení MATLAB je dostupné jako "online živé školení" nebo "na místě živé školení". Online živé školení (neboli "vzdálené živé školení") se provádí prostřednictvím interaktivní vzdálené plochy . Živá školení na místě lze provádět lokálně v prostorách zákazníka v České republice nebo ve firemních školicích střediscích NobleProg v České republice. NobleProg -- Váš místní poskytovatel školení
Dynamická analýza je proces testování a hodnocení materiálu nebo programu při spuštění softwaru.
Toto školení vedené instruktorem (online nebo na místě) je zaměřeno na vývojáře nebo inženýry na úrovni začátečníků, kteří se chtějí naučit používat numerickou simulaci pro dynamické problémy pomocí Matlabu.
Na konci tohoto školení budou účastníci schopni:
Pochopte základy dynamické analýzy.
Pomocí programu Matlab můžete provádět analytická a numerická řešení.
Odvozujte pohybové rovnice pomocí různých přístupů.
Formát kurzu
Interaktivní přednáška a diskuse.
Spousta cvičení a praxe.
Praktická implementace v prostředí živého testovacího prostředí.
Možnosti přizpůsobení kurzu
Chcete-li požádat o přizpůsobené školení pro tento kurz, kontaktujte nás a domluvte se.
In the first part of this training, we cover the fundamentals of MATLAB and its function as both a language and a platform. Included in this discussion is an introduction to MATLAB syntax, arrays and matrices, data visualization, script development, and object-oriented principles.
In the second part, we demonstrate how to use MATLAB for data mining, machine learning and predictive analytics. To provide participants with a clear and practical perspective of MATLAB's approach and power, we draw comparisons between using MATLAB and using other tools such as spreadsheets, C, C++, and Visual Basic.
In the third part of the training, participants learn how to streamline their work by automating their data processing and report generation.
Throughout the course, participants will put into practice the ideas learned through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough grasp of MATLAB's capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation.
Assessments will be conducted throughout the course to gauge progress.
Format of the Course
Course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation.
Note
Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange.
This instructor-led, live training in České republice (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.
This two-day course provides a comprehensive introduction to the MATLAB® technical computing environment. The course is intended for beginner users and those looking for a review. No prior programming experience or knowledge of MATLAB is assumed. Themes of data analysis, visualization, modeling, and programming are explored throughout the course.
This course contains a comprehensive material about MATLAB as a powerful simulation tool for communications. The aim of this course is to introduce MATLAB not only as a general programming language, rather, the role of the extremely powerful MATLAB capabilities as a simulation tool is emphasized. The examples given to illustrate the material of the course is not just a direct use of MATLAB commands, instead they often represent real problems.
This four day course provides image processing foundations using Matlab. You will practise how to change and enhance images and even extract patterns from the images. You will also learn how to build 2D filters and apply them on the images.
Examples and exercises demonstrate the use of appropriate Matlab and Image Processing Toolbox functionality throughout the analysis process.
Objective: This training is meant for software Engineers who are working with MBD technology, the training will cover Modelling techniques for Automotive systems, Automotive standards ,Auto-code generation and Model test harness building and verification Audience: Software developper for automotive supplier
Course is dedicated for those who would like to know an alternative program to the commercial MATLAB package. The three-day training provides comprehensive information on moving around the environment and performing the OCTAVE package for data analysis and engineering calculations. The training recipients are beginners but also those who know the program and would like to systematize their knowledge and improve their skills. Knowledge of other programming languages is not required, but it will greatly facilitate the learners' acquisition of knowledge. The course will show you how to use the program in many practical examples.
MATLAB integruje výpočet, vizualizace a programování do snadno použitelného prostředí. Nabízí Financial Toolbox, který zahrnuje funkce potřebné k provádění matematické a statistické analýzy finančních údajů, pak zobrazuje výsledky s grafickou kvalitou prezentace.
Tento výcvik vedený instruktorem poskytuje úvod do MATLAB pro finance. Ponoříme se do analýzy dat, vizualizace, modelování a programování prostřednictvím praktických cvičení a plnohodnotné praxe v laboratoři.
Na konci tohoto tréninku, účastníci budou mít důkladné pochopení silných funkcí zahrnutých v MATLAB's Financial Toolbox a získat potřebnou praxi, aby je aplikovat okamžitě pro řešení problémů v reálném světě.
publikum
Finanční odborníci s předchozím zkušeností s MATLAB
This course provides a comprehensive introduction to the MATLAB technical computing environment + an introduction to using MATLAB for financial applications. The course is intended for beginning users and those looking for a review. No prior programming experience or knowledge of MATLAB is assumed. Themes of data analysis, visualization, modeling, and programming are explored throughout the course. Topics include:
Working with the MATLAB user interface
Entering commands and creating variables
Analyzing vectors and matrices
Visualizing vector and matrix data
Working with data files
Working with data types
Automating commands with scripts
Writing programs with logic and flow control
Writing functions
Using the Financial Toolbox for quantitative analysis
Predictive analytics is the process of using data analytics to make predictions about the future. This process uses data along with data mining, statistics, and machine learning techniques to create a predictive model for forecasting future events.
In this instructor-led, live training, participants will learn how to use Matlab to build predictive models and apply them to large sample data sets to predict future events based on the data.
By the end of this training, participants will be able to:
Create predictive models to analyze patterns in historical and transactional data
Use predictive modeling to identify risks and opportunities
Build mathematical models that capture important trends
Use data from devices and business systems to reduce waste, save time, or cut costs
Audience
Developers
Engineers
Domain experts
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
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
Prescriptive analytics is a branch of business analytics, together with descriptive and predictive analytics. It uses predictive models to suggest actions to take for optimal outcomes, relying on optimization and rules-based techniques as a basis for decision making.
In this instructor-led, live training, participants will learn how to use Matlab to carry out prescriptive analytics on a set of sample data.
By the end of this training, participants will be able to:
Understand the key concepts and frameworks used in prescriptive analytics
Use MATLAB and its toolboxes to acquire, clean and explore data
Use rules-based techniques including inference engines, scorecards, and decision trees to make decisions based on different business scenarios
Use Monte Carlo simulation to analyze uncertainties and ensure sound decision making
Deploy predictive and prescriptive models to enterprise systems
Audience
Business analysts
Operations planners
Functional managers
BI (Business Intelligence) team members
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
This three-day course provides a comprehensive introduction to the MATLAB technical computing environment. The course is intended for beginning users and those looking for a review. No prior programming experience or knowledge of MATLAB is assumed. Themes of data analysis, visualization, modeling, and programming are explored throughout the course. Topics include:
Working with the MATLAB user interface
Entering commands and creating variables
Analyzing vectors and matrices
Visualizing vector and matrix data
Working with data files
Working with data types
Automating commands with scripts
Writing programs with logic and flow control
Writing functions
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