Basic MATLAB Programming Training Course

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.

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

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

Pada bagian pertama pelatihan ini, kami membahas dasar-dasar MATLAB dan fungsinya sebagai bahasa dan platform. Termasuk dalam diskusi ini adalah pengenalan MATLAB sintaksis, array dan matriks, visualisasi data, pengembangan skrip, dan prinsip-prinsip berorientasi objek.

Di bagian kedua, kami mendemonstrasikan cara menggunakan MATLAB untuk penambangan data, pembelajaran mesin, dan analisis prediktif. Untuk memberikan peserta perspektif yang jelas dan praktis tentang pendekatan dan kekuatan MATLAB, kami membuat perbandingan antara penggunaan MATLAB dan penggunaan alat lain seperti spreadsheet, C, C++, dan Visual Basic.

Pada bagian ketiga pelatihan, peserta belajar bagaimana menyederhanakan pekerjaan mereka dengan mengotomatiskan pemrosesan data dan pembuatan laporan.

Sepanjang kursus, peserta akan mempraktikkan ide-ide yang dipelajari melalui latihan langsung di lingkungan laboratorium. Di akhir pelatihan, peserta akan memiliki pemahaman menyeluruh tentang kemampuan MATLAB dan akan dapat menggunakannya untuk memecahkan masalah ilmu data di dunia nyata serta menyederhanakan pekerjaan mereka melalui otomatisasi.

Penilaian akan dilakukan sepanjang kursus untuk mengukur kemajuan.

Format Kursus

• Kursus mencakup latihan teoretis dan praktis, termasuk diskusi kasus, pemeriksaan kode sampel, dan implementasi langsung.

Catatan

• Sesi latihan akan didasarkan pada contoh templat laporan data yang telah diatur sebelumnya. Jika Anda memiliki persyaratan khusus, silakan hubungi kami untuk mengaturnya.

This instructor-led, live training in Indonesia (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 integrates computation, visualization and programming in an easy to use environment. It offers Financial Toolbox, which includes the features needed to perform mathematical and statistical analysis of financial data, then display the results with presentation-quality graphics.

This instructor-led training provides an introduction to MATLAB for finance. We dive into data analysis, visualization, modeling and programming by way of hands-on exercises and plentiful in-lab practice.

By the end of this training, participants will have a thorough understanding of the powerful features included in MATLAB's Financial Toolbox and will have gained the necessary practice to apply them immediately for solving real-world problems.

Audience

• Financial professionals with previous experience with MATLAB

Format of the course

• Part lecture, part discussion, heavy hands-on practice

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

MATLAB adalah lingkungan komputasi numerik dan bahasa pemrograman yang dikembangkan oleh MathWorks.

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

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.

Kursus ini dirancang untuk mengajarkan dasar-dasar Bahasa Systems Modeling (SysML), penerapannya melalui perangkat lunak MagicDraw/Cameo, teknik simulasi Rekayasa Sistem Berbasis Model (MBSE) dasar, dan praktik terbaik dalam MBSE. Pelatihan ini juga dirancang untuk memberikan para profesional latar belakang di balik simulasi arsitektur, pengenalan plugin Simulation Toolkit, simulasi berbagai jenis diagram, dan cara menggabungkan simulasi diagram bersama-sama untuk mengotomatiskan arsitektur .

Kursus didedikasikan bagi mereka yang ingin mengetahui program alternatif selain paket komersial MATLAB. Pelatihan tiga hari ini memberikan informasi komprehensif tentang pergerakan lingkungan dan melakukan paket OCTAVE untuk analisis data dan perhitungan teknik. Penerima pelatihan adalah para pemula namun juga mereka yang mengetahui program ini dan ingin mensistematisasikan pengetahuannya serta meningkatkan keterampilannya. Pengetahuan tentang bahasa pemrograman lain tidak diperlukan, tetapi akan sangat memudahkan perolehan pengetahuan pembelajar. Kursus ini akan menunjukkan kepada Anda cara menggunakan program ini dalam banyak contoh praktis.

This instructor-led, live training in Indonesia (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 graphical programming environment for modeling, simulating and analyzing multidomain dynamic systems.

Kursus ini berisi materi komprehensif tentang MATLAB sebagai alat simulasi yang ampuh untuk komunikasi. Tujuan kursus ini adalah untuk memperkenalkan MATLAB tidak hanya sebagai bahasa pemrograman umum, melainkan, peran kemampuan MATLAB yang sangat ampuh sebagai alat simulasi ditekankan. Contoh-contoh yang diberikan untuk mengilustrasikan materi kursus ini bukan hanya penggunaan langsung perintah MATLAB, melainkan sering kali menggambarkan masalah nyata.