MATLAB Master Class: Go from Beginner to Expert in MATLAB

MATLAB from beginner to advance level with Advanced Data Types and Applications from Data Science and Data preprocessing

What you'll learn

Develop beginer to advance level skills of Programming with MATLAB. This is the only course which enables you to learn intermediate and advance programming data structures such as structures, tables, times tables, cells and map container.
Gain Hands-On experience with MATLAB for visualizing, analyzing and formulating intermediate and some advanced level problems using MATLAB programming skills
Experience some real world applications of MATLAB in solving Data Science problems.


Requirements

We cover everything from scratch and therefore do not require any prior knowledge of MATLAB
The installation of MATLAB software on your machine is a must for this course so that you are able to run the commands and scripts that we cover during the course. If you do not have the MATLAB software installed than you may consider the following options
1. You may download a free trail copy of the software from the MATHWORK website. This is for limited time use
2. If you are student or employee, you may contact your School or employer for a free copy. Many universities offer a free student version of the software
3. You may consider downloading the Octave which is a free and has nearly identical functionality as that of MATLAB. (I would not recommend this option since you may not be able to have access to all the functions that we cover in this course)
4. If none of the above works for you, then you may purchase the student version directly from Mathworks website which is significantly lower in cost compare to its full version

Description

Basic Course Description

MATLAB (matrix laboratory) is one of the fundamental and leading programming language and is a must learn skill for anyone who want to develop a career in engineering, science or related fields. Excellent MATLAB programming skills is therefore a crucial factor in making or breaking your career.

This course is designed from a perspective of a student who has no prior knowledge of MATLAB. The course starts from the very basic concepts and then built on top of those basic concepts and move towards more advanced topics such as visualization, exporting and importing of data, advance data types and data structures and advance programming constructs.

To get the real feel of MATLAB in solving and analyzing real life problems, the course includes machine learning topics in data science and data preprocessing. To convert the source codes into meaningful pieces of softwares, the course also covers topics in building GUI's using GUIDE and App Designer utilities of matlab. Finally, we also cover topics in text processing such as building Regular Expressions.

The course is fun and exciting, but at the same time we dive deep into MATLAB to uncover its power of formulating and analyzing real life problems. The course is structured into four different Parts. Below is the detailed outline of this course.

Part 1: MATLAB from Beginer to Advance

Segment 1.1: Handling variables and Creating Scripts

Segment 1.2: Doing Basic Maths in MATLAB

Segment 1.3: Operations on Matrices

Segment 1.4: Advance Math Functions with Symbolic Data Type

Segment 1.5: Interacting with MATLAB and Graphics

Segment 1.6: Importing Data into MATLAB

Segment 1.7: File Handling and Text Processing

Segment 1.8: MATLAB Programming

Segment 1.9: Sharing Your MATLAB Results

Part 2: Advance MATLAB Data Types

Segment 2.1: Cell Data Type

Segment 2.2: Tables and Time Tables

Segment 2.3: Working with Structures and Map Container Data Type

Segment 2.4: Converting between Different Data Types


Part 3: Machine Learning for Data Science Using MATLAB

Segment 3.1 Data Preprocessing

Segment 3.2. Classification

Segment 3.2.1 K-Nearest Neighbor

Segment 3.2.2 Naive Bayes

Segment 3.2.3 Decision Trees

Segment 3.2.4 Support Vector Machine

Segment 3.2.5 Discriminant Analysis

Segment 3.2.6 Ensembles

Segment 3.2.7 Performance Evaluation

Segment 3.3 Clustering

Segment 3.3.1 K-Means

Segment 3.3.2 Hierarchical Clu stering

Segment 3.4 Dimensionality Reduction

Segment 3.5 Project


Part 4: Data Preprocessing for Machine Learning using MATLAB

Segment 4.1 Handing Missing Values

Segment 4.2 Dealing with Categorical Variables

Segment 4.3 Outlier Detection

Segment 4.4 Feature Scaling and Data Discretization

Segment 4.5 Selecting the Right Method for your Data


Part 5: Build Regular Expression using MATLAB for Text Processing

Segment 5.1 : Introduction and getting started with regexes

Segment 5.2: Character Classes

Segment 5.3: Anchors and Word Boundaries

Segment 5.4: Repetitiongs using Quantifiers

Segment 5.5: Group Constructs

Segment 5.6: Assertions, Conditions and Backreferencing

Segment 5.7: Practical Examples


Part 6: Matlab App Designing Using Guide

Segment 6.1: Basics of the GUIDE

Segment 6.2: Linking the Code with GUI

Segment 6.3: Advance Techniques for GUIDE

Segment 6.4: Sample Projects with GUIDE

Segment 6.5: More Useful Tricks and Examples with GUIDE


Part 7: Create MATLAB Apps with App Designer

Segment 7.1: Basics of App Designer

Segment 7.2: Tips and Tricks for Effective use of App Designer

Segment 7.3: Coding GUI's

Segment 7.4: Advance Techniques

Segment 7.5: Sample Projects with App Designer


Who this course is for:

Anyone looking to build a strong career in science or engineering through Excellent MATLAB coding skills
Anyone wanting to advance their skills of real world problem solving with MATLAB based scientific computing