Course Outline

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

Requirements

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

Audience

  • Developers
  • Data scientists
 35 Hours

Number of participants



Price per participant

Open Training Courses require 5+ participants.

Testimonials (5)

A lot of patience

Mateusz - WestWind Energy Polska Sp. z o.o.
Course - ArcGIS for Spatial Analysis

Machine Translated

The trainer adapted the materials and contents to what he thought would be best for us and he succeeded. The quality of the training was excellent.

Jorge Sanchez Hernandez - CSMART - Carnival
Course - QGIS for Geographic Information System

Professional and very practical, usuefull in a daily work

Jozefin Rékasi - SC Automobile Dacia SA
Course - Advanced Data Analysis with TIBCO Spotfire

It covered the areas i said i was interested in before the course: data relationships, using python script. Connecting to databases will be covered in the advanced module.

Cristian Tudose - SC Automobile Dacia SA
Course - Introduction to Spotfire

I genuinely enjoyed the lots of labs and practices.

Vivian Feng - Destination Canada
Course - Data Analysis with SQL, Python and Spotfire

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