Fundamental MATLAB Programming for AI

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Fundamental MATLAB Programming for AI

This course is part of Applied AI for Engineers and Scientists: Foundations Specialization

Instructor: Bo Liu

2,014 already enrolled

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3 modules

Gain insight into a topic and learn the fundamentals.

76 reviews

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

76 reviews

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Learn MATLAB fundamentals, particularly those that are useful for applying AI techniques using MATLAB.

Skills you'll gain

Tools you'll learn

Matlab

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

3 assignments

Taught in English

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This course is part of the Applied AI for Engineers and Scientists: Foundations Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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Gain a foundational understanding of a subject or tool
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There are 3 modules in this course

This course introduces the fundamentals of the programming platform of this course, MATLAB. Through MATLAB’s toolboxes, engineers can make use of AI techniques bypassing intricate programming and achieve superior results. After learning this course (3 modules), students will be ready to learn AI techniques using MATLAB in terms of programming skills.

In this course, MATLAB fundamentals, particularly those that are useful for applying AI techniques using MATLAB, are introduced. This includes manipulating variables and matrices in MATLAB, MATLAB scripts, graphs, using built-in functions, defining and using custom functions, conditionals and program control, loops, table arrays and cell arrays to manipulate data, categorical data and one-hot encoding of them, etc. Case studies will be provided for writing objective functions in engineering optimization and data cleaning for building machine learning models, which are the fundamentals of Courses 2 and 3. In partnership with MathWorks, enrolled students have access to MATLAB for the duration of the course.

This module introduces the fundamentals of the programming platform of this course, MATLAB. Through MATLAB’s toolboxes for engineering and scientific modeling and AI techniques, students can bypass intricate programming and achieve superior results. After learning this module, students will be able to:

What's included

16 videos9 readings1 assignment4 app items1 discussion prompt

16 videosTotal 110 minutes

Welcome to the specialization - Applied AI for Engineers and Scientists: Foundations6 minutes
Introduction to Course 1 and Week 1's Study3 minutes
MATLAB Basics: The Computing Environment12 minutes
Tutorial: MATLAB Basics7 minutes
Tutorial: MATLAB LiveScript7 minutes
MATLAB Basics: Using Built-in Functions3 minutes
MATLAB Matrices: Enter a Matrix8 minutes
MATLAB Matrices: Access Elements in a Matrix5 minutes
MATLAB Matrices: Manipulate Matrices8 minutes
MATLAB Built-in Functions: Data Types, Matrix Operations, and Statistics9 minutes
MATLAB Built-in Functions: Matrix Tiling, Sorting, and Random Number Generation6 minutes
MATLAB Scripts: Introduction to MATLAB Scripts5 minutes
Tutorial: MATLAB Debug Example10 minutes
MATLAB Graphics: Plotting Basics and Customization6 minutes
MATLAB Graphics: Improving the Plots6 minutes
Platform to Do Exercises and Assignments7 minutes

9 readingsTotal 71 minutes

Specialization and Course Structure5 minutes
Specialization Sample Certificate1 minute
How to Access MATLAB Online5 minutes
Materials about MATLAB Basics10 minutes
Materials about MATLAB Matrices10 minutes
Materials about MATLAB Built-in Functions10 minutes
Materials about MATLAB Scripts10 minutes
Materials about MATLAB Graphics10 minutes
Exercise solutions10 minutes

1 assignmentTotal 15 minutes

Module 1 Quiz15 minutes

4 app itemsTotal 90 minutes

Module 1 Exercise 115 minutes
Module 1 Exercise 215 minutes
Module 1 Assignment 130 minutes
Module 1 Assignment 230 minutes

1 discussion promptTotal 10 minutes

Module 1 Discussion about MATLAB10 minutes

This module introduces conditionals and program control, loops, and MATLAB custom functions, followed by two case studies. After learning this module, students will be able to:

What's included

7 videos5 readings1 assignment4 app items1 discussion prompt

7 videosTotal 48 minutes

Module 2 Introduction to Week 2's Study1 minute
Custom MATLAB Functions: Creating Custom MATLAB Functions10 minutes
Custom MATLAB Functions: Anonymous Functions8 minutes
MATLAB Conditionals and Loops: Conditionals and Program Control in MATLAB8 minutes
MATLAB Conditionals and Loops: Loop in MATLAB Programming8 minutes
Case Study: Kepler's Third Law8 minutes
Case Study: The Newton Raphson Method6 minutes

5 readingsTotal 50 minutes

Materials about Custom and Anonymous Functions10 minutes
Materials about Conditionals and Loops10 minutes
Materials about Kepler's Third Law10 minutes
Materials about Newton Raphson Method10 minutes
Exercise Solutions10 minutes

1 assignmentTotal 30 minutes

Module 2 Quiz30 minutes

4 app itemsTotal 120 minutes

Module 2 Exercise 130 minutes
Module 2 Exercise 230 minutes
Module 2 Assignment 130 minutes
Module 2 Assignment 230 minutes

1 discussion promptTotal 10 minutes

Module 2 Discussion on functions, conditionals and loops10 minutes

This module introduces MATLAB data types and widely used functions in AI programs. Two case studies that are important for AI algorithms for optimization and machine learning in science and engineering are employed to practice students’ MATLAB programming skills and get ready for learning AI. After learning this module, students will be able to:

What's included

9 videos8 readings1 assignment3 app items

9 videosTotal 61 minutes

Module 3 Introduction to Week 3's Study1 minute
MATLAB Table and Cell Arrays: MATLAB Table Arrays11 minutes
MATLAB Table and Cell Arrays: Import/Export Tables5 minutes
MATLAB Table and Cell Arrays: MATLAB Cell Arrays9 minutes
Categorical Data: Categorical Data and One Hot Encoding12 minutes
Write an Objective Function: MSE and Rastrigin Benchmark Explained7 minutes
Write an Objective Function: Understanding and Implementing Binary Cross Entropy5 minutes
Data Cleaning: Essentials4 minutes
How to Use MATLAB Online for Module 3 Exercise 16 minutes

8 readingsTotal 53 minutes

Materials about MATLAB Table and Cell Arrays10 minutes
Materials about Categorical Data10 minutes
Materials about Objective Functions10 minutes
Materials about Data Cleaning10 minutes
CSV file in Exercise 11 minute
Exercise Solutions10 minutes
CSV file for Assignment 11 minute
CSV files for Assignment 21 minute

1 assignmentTotal 30 minutes

Module 3 Quiz30 minutes

3 app itemsTotal 90 minutes

Module 3 Exercise 130 minutes
Module 3 Assignment 130 minutes
Module 3 Assignment 230 minutes

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Instructor

Instructor ratings

(5 ratings)

Bo Liu

University of Glasgow

3 Courses3,570 learners

Offered by

University of Glasgow

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Reviewed on Nov 22, 2025

Thanks to this course, I'm no longer intimidated by MATLAB syntax. The conditional logic module was a lifesaver!

Reviewed on Dec 1, 2025

This course transformed my MATLAB skills from 'copy paste coding' to writing clean, efficient scripts with purpose.

Reviewed on Dec 1, 2025

The instructor's examples using real world engineering problems made abstract AI concepts feel totally achievable.

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