面向對象的Programming與MATLAB在地球物理學中的應用（基礎級）培訓

為期3天的課程，帶您瀏覽MATLAB主屏幕和窗口，包括......

• 如何使用matlab作為caluclator並繪製基本曲線
• 如何創建自己的自定義函數和腳本

這個為期四天的課程使用Matlab提供圖像處理基礎。您將練習如何更改和增強圖像，甚至從圖像中提取圖案。您還將學習如何構建2D濾鏡並將其應用於圖像。

示例和練習演示了在整個分析過程中使用適當的Matlab和圖像處理工具箱功能。

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

在本培訓的第一部分，我們將介紹 MATLAB 的基礎知識及其作為語言和平臺的功能。  本次討論包括對 MATLAB 語法、陣列和矩陣、數據可視化、腳本開發和面向對象原則的介紹。

在第二部分中，我們將演示如何使用 MATLAB 進行數據挖掘、機器學習和預測分析。為了向參與者提供一個清晰而實用的視角來瞭解 MATLAB 的方法和能力，我們將使用 MATLAB 與使用其他工具（如電子表格、C、C++ 和 Visual Basic）進行比較。

在培訓的第三部分，參與者學習如何通過自動化數據處理和報告生成來簡化他們的工作。

在整個課程中，參與者將通過實驗室環境中的實踐練習將學到的想法付諸實踐。在培訓結束時，參與者將全面掌握 MATLAB 的能力，並能夠利用它來解決現實世界的數據科學問題，以及通過自動化來簡化他們的工作。

將在整個課程中進行評估，以衡量進展情況。

課程形式

• 課程包括理論和實踐練習，包括案例討論、示例代碼檢查和動手實施。

注意

• 實踐課程將基於預先安排的樣本數據報告範本。如果您有具體要求，請聯繫我們安排。

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 是 MathWorks 開發的數值計算環境和程式設計語言。

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

這個為期兩天的課程全面介紹了MATLAB技術計算環境。本課程面向初學者和尋求評審的用戶。沒有先前的編程經驗或MATLAB知識。在整個課程中探索了數據分析，可視化，建模和編程的主題。

該課程專為那些想知道商業 MATLAB 包的替代程式的人而設計。為期三天的培訓提供了有關在環境中移動以及執行 OCTAVE 軟體包進行數據分析和工程計算的全面資訊。培訓接受者是初學者，但也有那些了解該計劃並希望將他們的知識系統化並提高技能的人。不需要其他程式設計語言的知識，但它將極大地促進學習者獲取知識。該課程將在許多實際範例中向您展示如何使用該程式。

這種以講師為主導的台灣現場培訓（現場或遠端）針對的是希望探索和/或過渡到Python進行數據分析和可視化的Matlab使用者。

在培訓結束時，參與者將能夠：

• 安裝和配置Python開發環境。
• 了解Matlab和Python語法之間的差異和相似之處。
• 使用Python從各種數據集中獲取洞察。
• 將現有的Matlab應用程序轉換為Python。
• 整合Matlab和Python應用程序。

Simulink是一個用於建模，模擬和分析多域動態系統的圖形化編程環境。

本課程包含有關 MATLAB 作為強大的通信模擬工具的綜合材料。本課程的目的不僅是介紹 MATLAB 作為一種通用的程式設計語言，而是強調極其強大的 MATLAB 功能作為類比工具的作用。為說明課程材料而給出的示例不僅僅是直接使用 MATLAB 命令，而是它們通常代表實際問題。

目標：此培訓適用於使用MBD技術的軟件工程師，培訓將涵蓋Automotive系統的建模技術， Automotive標準，自動代碼生成和模型測試工具構建和驗證受眾：汽車供應商的軟件開發人員