MATLAB Fundamentals, Data Science & Report Generation Treningskurs

Kurskode

matlabdsandreporting

Varighet

35 timer (vanligvis 5 dag inkludert pauser)

Krav

  • Knowledge of basic mathematical concepts such as linear algebra, probability theory and statistics
  • No previous experience with MATLAB is needed

Audience

  • Developers
  • Data scientists

Oversikt

I den første delen av denne opplæringen dekker vi grunnleggende om MATLAB og dens funksjon som både språk og plattform. Inkludert i denne diskusjonen er en introduksjon til MATLAB syntaks, matriser og matriser, datavisualisering, skriptutvikling og objektorienterte prinsipper.

I den andre delen demonstrerer vi hvordan du kan bruke MATLAB til data mining, maskinlæring og prediktiv analyse. For å gi deltakerne et klart og praktisk perspektiv på MATLAB tilnærming og kraft, trekker vi sammenligninger mellom bruk av MATLAB og bruk av andre verktøy som regneark, C, C++ og Visual Basic.

I den tredje delen av opplæringen lærer deltakerne å effektivisere arbeidet sitt ved å automatisere databehandlingen og rapporteringen.

Gjennom hele kurset vil deltakerne praktisere ideene som læres gjennom praktiske øvelser i et laboratoriemiljø. Ved slutten av opplæringen vil deltakerne ha et grundig grep om MATLAB evner og vil kunne bruke det til å løse reelle datavitenskapelige problemer, samt for å effektivisere arbeidet gjennom automatisering.

Vurderinger vil bli gjennomført i løpet av kurset for å måle fremgang.

Kursets format

  • Emnet inkluderer teoretiske og praktiske øvelser, inkludert saksdiskusjoner, prøvekodeinspeksjon og praktisk implementering.

Merk

  • Øvingsøkter vil være basert på forhåndsarrangerte maler for eksempeldata. Hvis du har spesifikke krav, kan du kontakte oss for å avtale det.

Machine Translated

Kursplan

Introduction
MATLAB for data science and reporting

 

Part 01: MATLAB Fundamentals

Overview

  • MATLAB for data analysis, visualization, modeling, and programming.

Working with the MATLAB user interface

Overview of MATLAB syntax

Entering commands

  • Using the command line interface

Creating variables

  • Numeric vs character data

Analyzing vectors and matrices

  • Creating and manipulating
  • Performing calculations

Visualizing vector and matrix data

Working with data files

  • Importing data from Excel spreadsheets

Working with data types

  • Working with table data

Automating commands with scripts

  • Creating and running scripts
  • Organizing and publishing your scripts

Writing programs with branching and loops

  • User interaction and flow control

Writing functions

  • Creating and calling functions
  • Debugging with MATLAB Editor

Applying object-oriented programming principles to your programs

 

Part 02: MATLAB for Data Science

Overview

  • MATLAB for data mining, machine learning and predictive analytics

Accessing data

  • Obtaining data from files, spreadsheets, and databases
  • Obtaining data from test equipment and hardware
  • Obtaining data from software and the Web

Exploring data

  • Identifying trends, testing hypotheses, and estimating uncertainty

Creating customized algorithms

Creating visualizations

Creating models

Publishing customized reports

Sharing analysis tools

  • As MATLAB code
  • As standalone desktop or Web applications

Using the Statistics and Machine Learning Toolbox

Using the Neural Network Toolbox

 

Part 03: Report Generation

Overview

  • Presenting results from MATLAB programs, applications, and sample data
  • Generating Microsoft Word, PowerPoint®, PDF, and HTML reports.
  • Templated reports
  • Tailor-made reports
    • Using organization’s templates and standards

Creating reports interactively vs programmatically

  • Using the Report Explorer
  • Using the DOM (Document Object Model) API

Creating reports interactively using Report Explorer

  • Report Explorer Examples
    • Magic Squares Report Explorer Example
  • Creating reports
    • Using Report Explorer to create report setup file, define report structure and content
  • Formatting reports
    • Specifying default report style and format for Report Explorer reports
  • Generating reports
    • Configuring Report Explorer for processing and running report
  • Managing report conversion templates
    • Copying and managing Microsoft Word, PDF, and HTML conversion templates for Report Explorer reports
  • Customizing Report Conversion templates
    • Customizing the style and format of Microsoft Word and HTML conversion templates for Report Explorer reports
  • Customizing components and style sheets
    • Customizing report components, define layout style sheets

Creating reports programmatically in MATLAB

  • Template-Based Report Object (DOM) API Examples
    • Functional report
    • Object-oriented report
    • Programmatic report formatting
  • Creating report content
    • Using the Document Object Model (DOM) API
  • Report format basics
    • Specifying format for report content
  • Creating form-based reports
    • Using the DOM API to fill in the blanks in a report form
  • Creating object-oriented reports
    • Deriving classes to simplify report creation and maintenance
  • Creating and formatting report objects
    • Lists, tables, and images
  • Creating DOM Reports from HTML
    • Appending HTML string or file to a Microsoft® Word, PDF, or HTML report generated by Document Object Model (DOM) API
  • Creating report templates
    • Creating templates to use with programmatic reports
  • Formatting page layouts
    • Formatting pages in Microsoft Word and PDF reports


Summary and Closing Remarks

Testimonials

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