Fundamental MATLAB Programming for AI

Fundamental MATLAB Programming for AI

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

Instructor: Bo Liu

Access provided by Marie Curie Alumni Association

1,934 already enrolled

3 modules

Gain insight into a topic and learn the fundamentals.

75 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.

75 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

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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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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 videos Total 110 minutes

Welcome to the specialization - Applied AI for Engineers and Scientists: Foundations 6 minutes
Introduction to Course 1 and Week 1's Study 3 minutes
MATLAB Basics: The Computing Environment 12 minutes
Tutorial: MATLAB Basics 7 minutes
Tutorial: MATLAB LiveScript 7 minutes
MATLAB Basics: Using Built-in Functions 3 minutes
MATLAB Matrices: Enter a Matrix 8 minutes
MATLAB Matrices: Access Elements in a Matrix 5 minutes
MATLAB Matrices: Manipulate Matrices 8 minutes
MATLAB Built-in Functions: Data Types, Matrix Operations, and Statistics 9 minutes
MATLAB Built-in Functions: Matrix Tiling, Sorting, and Random Number Generation 6 minutes
MATLAB Scripts: Introduction to MATLAB Scripts 5 minutes
Tutorial: MATLAB Debug Example 10 minutes
MATLAB Graphics: Plotting Basics and Customization 6 minutes
MATLAB Graphics: Improving the Plots 6 minutes
Platform to Do Exercises and Assignments 7 minutes

9 readings Total 71 minutes

Specialization and Course Structure 5 minutes
Specialization Sample Certificate 1 minute
How to Access MATLAB Online 5 minutes
Materials about MATLAB Basics 10 minutes
Materials about MATLAB Matrices 10 minutes
Materials about MATLAB Built-in Functions 10 minutes
Materials about MATLAB Scripts 10 minutes
Materials about MATLAB Graphics 10 minutes
Exercise solutions 10 minutes

1 assignment Total 15 minutes

Module 1 Quiz 15 minutes

4 app items Total 90 minutes

Module 1 Exercise 1 15 minutes
Module 1 Exercise 2 15 minutes
Module 1 Assignment 1 30 minutes
Module 1 Assignment 2 30 minutes

1 discussion prompt Total 10 minutes

Module 1 Discussion about MATLAB 10 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 videos Total 48 minutes

Module 2 Introduction to Week 2's Study 1 minute
Custom MATLAB Functions: Creating Custom MATLAB Functions 10 minutes
Custom MATLAB Functions: Anonymous Functions 8 minutes
MATLAB Conditionals and Loops: Conditionals and Program Control in MATLAB 8 minutes
MATLAB Conditionals and Loops: Loop in MATLAB Programming 8 minutes
Case Study: Kepler's Third Law 8 minutes
Case Study: The Newton Raphson Method 6 minutes

5 readings Total 50 minutes

Materials about Custom and Anonymous Functions 10 minutes
Materials about Conditionals and Loops 10 minutes
Materials about Kepler's Third Law 10 minutes
Materials about Newton Raphson Method 10 minutes
Exercise Solutions 10 minutes

1 assignment Total 30 minutes

Module 2 Quiz 30 minutes

4 app items Total 120 minutes

Module 2 Exercise 1 30 minutes
Module 2 Exercise 2 30 minutes
Module 2 Assignment 1 30 minutes
Module 2 Assignment 2 30 minutes

1 discussion prompt Total 10 minutes

Module 2 Discussion on functions, conditionals and loops 10 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 videos Total 61 minutes

Module 3 Introduction to Week 3's Study 1 minute
MATLAB Table and Cell Arrays: MATLAB Table Arrays 11 minutes
MATLAB Table and Cell Arrays: Import/Export Tables 5 minutes
MATLAB Table and Cell Arrays: MATLAB Cell Arrays 9 minutes
Categorical Data: Categorical Data and One Hot Encoding 12 minutes
Write an Objective Function: MSE and Rastrigin Benchmark Explained 7 minutes
Write an Objective Function: Understanding and Implementing Binary Cross Entropy 5 minutes
Data Cleaning: Essentials 4 minutes
How to Use MATLAB Online for Module 3 Exercise 1 6 minutes

8 readings Total 53 minutes

Materials about MATLAB Table and Cell Arrays 10 minutes
Materials about Categorical Data 10 minutes
Materials about Objective Functions 10 minutes
Materials about Data Cleaning 10 minutes
CSV file in Exercise 1 1 minute
Exercise Solutions 10 minutes
CSV file for Assignment 1 1 minute
CSV files for Assignment 2 1 minute

1 assignment Total 30 minutes

Module 3 Quiz 30 minutes

3 app items Total 90 minutes

Module 3 Exercise 1 30 minutes
Module 3 Assignment 1 30 minutes
Module 3 Assignment 2 30 minutes

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Instructor

Instructor ratings

(5 ratings)

Bo Liu

University of Glasgow

3 Courses 3,226 learners

Offered by

University of Glasgow

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Reviewed on Nov 22, 2025

I never realized how intuitive MATLAB could be for AI until this course. The instructors made it feel like second nature!

Reviewed on Dec 1, 2025

This course is a must for engineers and scientists aiming to harness MATLAB’s powerful tools for AI development ,Clear explanations and hands-on coding sessions made complex concepts intuitive.

Reviewed on Nov 22, 2025

Modules on matrix manipulation and custom functions transformed how I approach data preprocessing for ML models. Highly recommended!

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