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Course Outline

Introduction
MATLAB for data science and reporting

Part 01: MATLAB Fundamentals

Overview

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

Working with the MATLAB user interface

Overview of MATLAB syntax

Entering commands

  • Navigating the command line interface.

Creating variables

  • Distinguishing between numeric and character data.

Analyzing vectors and matrices

  • Creation and manipulation of data structures.
  • Execution of calculations.

Visualizing vector and matrix data

Working with data files

  • Importing data from Excel spreadsheets.

Working with data types

  • Manipulating table data.

Automating commands with scripts

  • Creating and executing scripts.
  • Organizing and publishing scripts.

Writing programs with branching and loops

  • Managing user interaction and control flow.

Writing functions

  • Creating and invoking functions.
  • Debugging using the MATLAB Editor.

Applying object-oriented programming principles to your programs

Part 02: MATLAB for Data Science

Overview

  • Applying MATLAB for data mining, machine learning, and predictive analytics.

Accessing data

  • Retrieving data from files, spreadsheets, and databases.
  • Acquiring 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 derived from MATLAB programs, applications, and sample data.
  • Generating reports in Microsoft Word, PowerPoint®, PDF, and HTML formats.
  • Utilizing templated reports.
  • Creating tailor-made reports
    • Adhering to organizational 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 establish the report setup file, define structure, and specify content.
  • Formatting reports
    • Setting default report styles and formats for Report Explorer outputs.
  • Generating reports
    • Configuring Report Explorer to process and run the report.
  • Managing report conversion templates
    • Copying and managing conversion templates for Word, PDF, and HTML outputs for Report Explorer reports.
  • Customizing Report Conversion templates
    • Adjusting the style and format of Word and HTML conversion templates for Report Explorer reports.
  • Customizing components and style sheets
    • Modifying report components and defining layout style sheets.

Creating reports programmatically in MATLAB

  • Template-Based Report Object (DOM) API Examples
    • Functional reports.
    • Object-oriented reports.
    • Programmatic report formatting.
  • Creating report content
    • Utilizing the Document Object Model (DOM) API.
  • Report format basics
    • Defining the format for report content.
  • Creating form-based reports
    • Filling in report form blanks using the DOM API.
  • Creating object-oriented reports
    • Deriving classes to simplify report creation and maintenance.
  • Creating and formatting report objects
    • Handling lists, tables, and images.
  • Creating DOM Reports from HTML
    • Appending HTML strings or files to Word, PDF, or HTML reports generated via the Document Object Model (DOM) API.
  • Creating report templates
    • Developing templates for use with programmatic reports.
  • Formatting page layouts
    • Formatting pages in Word and PDF reports.


Summary and Closing Remarks

Requirements

  • Proficiency in basic mathematical concepts, including linear algebra, probability theory, and statistics.
  • No prior experience with MATLAB is required.

Audience

  • Developers
  • Data scientists
 35 Hours

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