Course Details

MATLAB Course

Course description

This course site is the result of several iterations of an introductory course I have given at MIT, the last of which was called DR. MATLAB. In that course I strived to change the usual pattern of teaching/learning MATLAB from a programming view point to a mathematical one. The idea is that by thinking about mathematical problems, students are prodded into learning MATLAB for the purpose of solving the problem at hand. The down-side to this approach is that it is somewhat based on the idea that people are already excited about mathematics, or can be excited about it. That said, as I taught the course at MIT, it was not a big problem.

Variables, arrays, conditional statements, loops, functions, and plots are covered in a project-based style where much of the learning happens away from the classroom. Students are expected to spend about 4 hours per week on homework. At the end of the course, students should be able to use MATLAB in their own work, and be prepared to deepen their MATLAB programming skills and tackle other languages for computing, such as Java, C++, or Python.

Course Outline

• Working with the MATLAB User Interface

Objective: Become familiar with the main features of the MATLAB integrated design environment and its user interfaces. Get an overview of course themes.

· Reading data from files

· Saving and loading variables

· Plotting data

· Customizing plots

· Exporting graphics for use in other applications

• Variables and Commands

Objective: Enter MATLAB commands, with an emphasis on creating variables, accessing and manipulating data in variables, and creating basic visualizations. Collect MATLAB commands into scripts for ease of reproduction and experimentation.

· Entering commands

· Creating numeric and character variables

· Making and annotating plots

· Getting help

· Creating and running live scripts

• Analysis and Visualization with Vectors

Objective: Perform mathematical and statistical calculations with vectors. Use MATLAB syntax to perform calculations on whole data sets with a single command. Organize scripts into logical sections for development, maintenance, and publishing.

· Performing calculations with vectors

· Accessing and modifying values in vectors

· Formatting and sharing live scripts

• Analysis and Visualization with Matrices

Objective: Use matrices as mathematical objects or as collections of (vector) data. Understand the appropriate use of MATLAB syntax to distinguish between these applications.

· Creating and manipulating matrices

· Performing calculations with matrices

· Calculating statistics with matrix data

· Visualizing matrix data

• Tables of Data

Objective: Import data as a MATLAB table. Work with data stored as a table.

· Storing data as a table

· Operating on tables

· Extracting data from tables

· Modifying tables

• Conditional Data Selection

Objective: Extract and analyze subsets of data that satisfy given criteria.

· Logical operations and variables

· Finding and counting

· Logical indexing

• Organizing Data

Objective: Organize table data for analysis. Represent data using appropriate native MATLAB data types.

· Combining tables of data

· Table metadata

· Dates and durations

· Discrete categories

• Analyzing Data

Objective: Perform typical data analysis tasks in MATLAB, including importing data from files, preprocessing data, fitting a model to data, and creating a customized visualization of the model.

· Importing from spreadsheets and delimited text files

· Dealing with missing data

· Plotting functions

· Customizing plots

• Increasing Automation with Programming Constructs

Objective: Create flexible code that can interact with the user, make decisions, and adapt to different situations.

· Programming constructs

· User interaction

· Decision branching

· Loops

• Increasing Automation with Functions

Objective: Increase automation by encapsulating modular tasks as user-defined functions. Understand how MATLAB resolves references to files and variables. Use MATLAB development tools to find and correct problems with code.

· Creating functions

· Calling functions

· Setting the MATLAB path

· Debugging

· Using breakpoints

· Creating and using structures