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MATLAB for Data Processing and Visualization
Data Analysis and Machine Learning, Fintech
MATLAB for Data Processing and Visualization
Learn how to automate importing data, analysis, processing, and creating custom visualizations with MATLAB
Course
Highlights
This one-day course focuses on importing and preparing data for data analytics applications. The course is intended for data analysts and data scientists who need to automate the processing, analysis, and visualization of data from multiple sources. Topics include:
- Importing data
- Processing data
- Customizing visualizations
- Working with irregular data
Who Should
Attend
Engineer, researchers, data scientists, and managers, who are involved in the process of preprocessing of the mixture data types measurement data and irregular data and to create customized.
Course
Prerequisites
MATLAB Fundamentals
Course
Benefits
Upon the completion of the course, the participants will be able to work with text files with arbitrary formatting and work with graphic object properties to customize the plots.
Partners
Upcoming Program
- Please keep me posted on the next schedule
- Please contact me to arrange customized/ in-house training
Course Outline
Importing Data
Objective: Read text files that contain a mixture of data types, delimiters, and headers.
- Import a mixture of data types from arbitrarily formatted text files
- Import only required columns of data from a text file
- Import and merge data from multiple files
Processing Data
Objective: Process raw imported data by extracting, manipulating, aggregating, and counting portions of data.
- Process data with missing elements
- Create and modify categorical arrays
- Aggregate, bin, and count groups of data
Customizing Visualizations
Objective: Annotate and modify standard plots to produce informative customized graphics.
- Determine properties of graphics objects and their associated values
- Locate and manipulate graphics objects
- Customize plots by modifying properties of graphics objects
- Interpolate irregularly spaced three-dimensional data
- Visualize three-dimensional data in two and three dimensions
Working with Irregular Data
Objective: Import and visualize scattered data from text files with irregular formatting.
- Parse text files to determine formatting
- Import data from separate sections of a text file
- Extract data from container variables
- Perform calculation on time series data