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
Testimonials (5)
very interactive...
Richard Langford
Course - SMACK Stack for Data Science
Younes is a great trainer. Always willing to assist, and very patient. I will give him 5 stars. Also, the QLIK sense training was excellent, due to an excellent trainer.
Dietmar Glanninger - BMW
Course - Qlik Sense for Data Science
Trainer was accommodative. And actually quite encouraging for me to take up the course.
Grace Goh - DBS Bank Ltd
Course - Python in Data Science
Subject presentation knowledge timing
Aly Saleh - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
It is great to have the course custom made to the key areas that I have highlighted in the pre-course questionnaire. This really helps to address the questions that I have with the subject matter and to align with my learning goals.
