Matlab Master Class: Go From Beginner To Expert In Matlab

MATLAB programming, data structures, apps, data science, regular expressions, text processing, task automation

What you'll learn
Develop beginer to advance level skills of Programming with MATLAB
Create a portfolio of Many MATLAB projects to apply for MATLAB jobs
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 problems
Be able to use MATLAB for data science and machine learning
Build GUIs and Desktop applications with MATLAB
Build power regexes and use them to identify patterns in the input text
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. At 37+ hours of video tutorials, this MATLAB course is one of the most comprehensive MATLAB course online which will take from beginner to professional.  This course is designed from a perspective of a student who has no prior knowledge of MATLAB and who is a MATLAB beginner. Throughout this comprehensive course, we cover a massive amount of skills and techniques including:Basic maths and matrix manipuation functionsData import and visualization MATLAB Programming, problem solving , logic development and the use of customized functionsSymbolic functions and variables for advance math operationsFile and directory handlingLive scripts and sharing of resultsAdvance data types including cells, tables, time tables and map containersData science classification, clustering and dimensionality reduction with MATLAB Essential data preprocessing tasks such as outliers, missing values, categorical attributes handlingBuilding regular expressions for textual processingBuilding GUIs using Guide and AppDesigner Automating tasks by controlling mouse, keyboard, running scripts from command window, batch filesWeb, email and other internet related operations Generating ppts, word files and pdfsCode debugger and analyzer, exception handling, startup, finish and diary functions. The course ensures that you learn by including Practice exercise questions along with solutions Challenging Exercise Questions Quizes andTakeaway code templates By taking this course, you will become a fluent MATLAB programmer and you'll be so good so that you can get a reasonable job offer as a MATLAB developer and use the language professionally.Don't just rely on my word, check what some of our existing students have to say about the same course"I had viewed the video in the propose sequence, as well, as I had looked at some videos outside of the instructor propose sequence, and only had one thing to say: - This course is excellent!!!!!!!!!!!!!"  Gabriel Federo Hungria"I have gone through the course on MATLAB Gui by the instructor. It was an A++ experience. He is the best instructor, really professional and knows exactly what to teach. Thanks for your wonderful contribution to help us understand MATLAB." Kunal Singh"Very interesting course, complete functionality of Matlab was explained and the quizzes further helped with the learning process." Hassan AyubPleaset note… I am very confident that you will like the course and therefore provides you with a FULL money back guarantee for 30 days! So there is a ZERO risk and nothing to loose. Finally, i am super excited to teach you matlab, so hit enroll and enjoy learning MATLAB

Overview

Section 1: Course and Instructor Introduction

Lecture 1 Course Introduction

Lecture 2 MATLAB Software (Pricing and Online resources)

Lecture 3 Download All the Codes and Data in a Single Click

Section 2: –––––– Part 1: MATLAB from Beginer to Advance ––––––––-

Lecture 4 MATLAB Graphical User Interface

Lecture 5 Tell us About the Course

Lecture 6 Some Common Operations

Section 3: 1.1: Handling variables and Creating Scripts

Lecture 7 Code and Scripts

Lecture 8 Let's lay foundations for understanding Variables

Lecture 9 Different types of variables (Strings, characters and logical)

Lecture 10 Creating scripts and understanding commenting and semicolon effect

Lecture 11 Data selection with the colon operator

Section 4: 1.2: Doing Basic Maths in MATLAB

Lecture 12 Code and Scripts

Lecture 13 Basic maths operations: addition, multiplication, subtraction and powers

Lecture 14 Basic maths operations: computing GCD, LCM, permutations and prime numbers

Lecture 15 Trignometric math functions

Lecture 16 Set operations (Union, intersection, complement and others)

Lecture 17 Computing statistics of the matrices

Lecture 18 Handling random numbers

Lecture 19 Cross product and dot product

Lecture 20 Basic logical operation (And, Or and Not)

Lecture 21 Sign and absolute functions

Lecture 22 Converting numbers between different bases

Lecture 23 Discretizing your data

Section 5: 1.3: Operations on Matrices

Lecture 24 Code and Scripts

Lecture 25 Computing unique elements

Lecture 26 Determining membership of elements to a matrix

Lecture 27 Shifting matrix elements

Lecture 28 Determinant, inverse and diagnal elements

Lecture 29 Relational operations

Lecture 30 Commonly used Matrices

Lecture 31 Sorting matrix values

Lecture 32 Size and length computation

Lecture 33 Concatenating Matrices

Lecture 34 Finding non-zero elements

Lecture 35 Frequency of values within a vector

Section 6: Section 1.4: Lets Learn Problem Solving and Have Some Practice

Lecture 36 A Three Step Problem Solving Strategy

Lecture 37 Sum of Multiples

Lecture 38 Sum Squares Difference

Lecture 39 Prime Factors of a Number

Lecture 40 Digits Multiplication of a Number

Section 7: 1.5: Advance Math Functions with Symbolic Data Type

Lecture 41 Code and Scripts

Lecture 42 Symbolic variables

Lecture 43 Differentiation and Integration using symbolic variables

Lecture 44 Solving Equations

Lecture 45 Symbolic Functions

Section 8: 1.6: Interacting with MATLAB and Graphics

Lecture 46 Code and Scripts

Lecture 47 Input output commands

Lecture 48 More input output commands

Lecture 49 Plotting data with MATLAB

Lecture 50 Plotting 3-D data

Lecture 51 More on plotting options

Lecture 52 Bar graphs

Lecture 53 Combining plots with hold on

Lecture 54 Interacting with the plot using the brush tool

Lecture 55 Two y-axis on the same plot

Lecture 56 Animated Line

Lecture 57 Checking for existence of scripts, files, folders, variables or functions

Lecture 58 Manipulating Directory (Part 1)

Lecture 59 Manipulating Directory (Part 2)

Lecture 60 Processing text files

Lecture 61 Project: Processing text file and visualizing its results

Lecture 62 Project solution

Section 9: 1.7: Importing Data into MATLAB

Lecture 63 Code and Scripts

Lecture 64 Importing data from excel into MATLAB

Lecture 65 Importing data in different formats (N)

Lecture 66 Spread Sheet link (Introduction and installation)

Lecture 67 Passing data between excel and MATLAB

Lecture 68 Calling MATLAB functions from Excel

Section 10: 1.8a: MATLAB Programming

Lecture 69 Code and Scripts

Lecture 70 Conditional if Statements (Part 1)

Lecture 71 Conditional if statment (Part 2)

Lecture 72 For loops for interating through your code

Lecture 73 Nested For Loops

Lecture 74 While loops (when you don't know the number of iterations)

Lecture 75 Breaking out from a loop before final condition

Lecture 76 Continue statement for skipping an iteration

Lecture 77 Switch statements for choice selection

Lecture 78 Test yourself: Have fun with some practice questions

Lecture 79 Solutions to practice exercise questions

Lecture 80 Q2: Solution Explaination (Concentric Rings Problems-Part-1)

Lecture 81 Q2: Solution Explaination (Concentric Rings Problems- Part-2)

Lecture 82 Q4: Solution Explaination (Back and Forth Numbers)

Lecture 83 Q6: Solution Explaination (Alternating Ones and Zeros)

Lecture 84 Test Yourself (Challenge): Have fun with Some Practice Questions

Lecture 85 More Challenging Questions and their Solutions

Section 11: Section 1.8b: Polishing Programming Skills with More Practice

Lecture 86 Nth prime number

Lecture 87 Next Prime

Lecture 88 Nth Prime Number Additional Explaination

Lecture 89 Next Four Prime Numbers

Lecture 90 Longest Chain (Part 1)

Lecture 91 Longest Chain (Part 2)

Lecture 92 Pandigital Numbers

Lecture 93 Refining the Code of Pandigital Numbers

Lecture 94 Triangle Numbers (Part 1)

Lecture 95 Triangle Numbers (Part 2)

Lecture 96 Pythagorean Triplet (Part 1)

Lecture 97 Pythagorean Triplet (Part 2)

Lecture 98 Number with Same Digits

Lecture 99 Even Fibonacci

Lecture 100 Highly Divisible Summation Numbers

Section 12: 1.8: Making your own functions

Lecture 101 Code and Scripts

Lecture 102 Creating Custom built Functions

Lecture 103 Functions with inputs

Lecture 104 Functions with multiple inputs and outputs

Lecture 105 Returning from a function

Lecture 106 Test Yourself: Have some fun with Practice Exercise Question

Lecture 107 Solutions to practice exercise questions

Section 13: 1.9: Sharing your MATLAB Results

Lecture 108 Code and Scripts

Lecture 109 Sharing results with automatically generated reports

Lecture 110 Sharing your results with live scripts

Section 14: –––––– Part 2: Advance MATLAB Data Types –––––––––––

Lecture 111 Introduction to the section

Section 15: 2.1: Cell Data Type

Lecture 112 Codes and Data

Lecture 113 Creating and defining cells

Lecture 114 Accessing Data in a Cell

Lecture 115 Adding and deleting elements from a cell

Lecture 116 Concatenating cells and passing cell contents to a function

Section 16: 2.2: Tables and Time Tables

Lecture 117 Codes and data

Lecture 118 Creating Tables

Lecture 119 Adding Descriptions, Units and Accessing individual columns

Lecture 120 Selecting and reordering rows

Lecture 121 Sorting rows or a table

Lecture 122 Setting Different properties of a table

Lecture 123 Reading and writing tables to memory

Lecture 124 Storing summary of a table

Lecture 125 Adding and deleting rows from a table

Lecture 126 Adding and deleting columns from a table

Lecture 127 Dealing with missing data

Lecture 128 Creating time tables

Lecture 129 Properties, sorting and data selection in time tables

Lecture 130 Concatenating time tables

Lecture 131 Indexing and retrieving data based on row times

Section 17: 2.3: Working with Structures and Map Container Data Type

Lecture 132 Codes and Data

Lecture 133 Creating structures

Lecture 134 Retrieving data from a field of a structure

Lecture 135 Concatenating structures

Lecture 136 Storing data from a structure field into a variable

Lecture 137 More operations on a structure

Lecture 138 Creating Map Containers

Lecture 139 Concatenation and more operations on map container

Section 18: 2.4: Data Types Conversions

Lecture 140 Codes and Data

Lecture 141 Converting other data types to cell

Lecture 142 Converting Cell to other Data Types

Lecture 143 Converting from other to table data type

Lecture 144 Converting from table to other data type

Section 19: –––––- Part 3: Machine Learning for Data Science using MATLAB ––––––

Lecture 145 Introduction to the segment

Section 20: 3.1: Data Preprocessing

Lecture 146 Code and Data

Lecture 147 Importing the Dataset

Lecture 148 Removing Missing Data (Part 1)

Lecture 149 Removing Missing Data (Part 2)

Lecture 150 Feature Scaling

Lecture 151 Handling Outliers (Part 1)

Lecture 152 Handling Outliers (Part 2)

Lecture 153 Dealing with Categorical Data (Part 1)

Lecture 154 Dealing with Categorical Data (Part 2)

Lecture 155 Your Preprocessing Template

Section 21: 3.2: Classification

Lecture 156 Code and Data

Section 22: 3.2.1: K-Nearest Neighbor

Lecture 157 KNN Intuition

Lecture 158 KNN in MATLAB (Part 1)

Lecture 159 KNN in MATLAB (Part 2)

Lecture 160 Visualizing the Decision Boundaries of KNN

Lecture 161 Explaining the code for visualization

Lecture 162 Here is our classification template

Lecture 163 How to change default options and customize classifiers

Lecture 164 Customization options for KNN

Section 23: 3.2.2: Naive Bayes

Lecture 165 Naive Bayesain Intuition (Part 1)

Lecture 166 Naive Bayesain Intuition (Part 2)

Lecture 167 Naive Bayesain in MATLAB

Lecture 168 Customization Options for Naive Bayesain

Section 24: 3.2.3: Decision Trees

Lecture 169 Decision trees intuition

Lecture 170 Decision Trees in MATLAB

Lecture 171 Visualizing Decision Trees using the View Function

Lecture 172 Customization Options for Decision Trees

Section 25: 3.2.4: Support Vector Machines

Lecture 173 SVM Intuition

Lecture 174 Kernel SVM Intuition

Lecture 175 SVM in MATLAB

Lecture 176 Customization Options for SVM

Section 26: 3.2.5: Discriminant Analysis

Lecture 177 Discriminant Analysis Intuition

Lecture 178 Discriminant Analysis in MATLAB

Lecture 179 Customization Options for Discriminant Analysis

Section 27: 3.2.6: Ensembles

Lecture 180 Ensembles Intuition

Lecture 181 Ensembles in MATLAB

Lecture 182 Customization options for Ensembles

Section 28: 3.2.7: Performance Evaluation

Lecture 183 Evaluating Classifiers: Confusion matrix (Theory)

Lecture 184 Validation Methods (Theory)

Lecture 185 Validation methods in MATLAB (Part 1)

Lecture 186 Validation methods in MATLAB (Part 2)

Lecture 187 Evaluating Classifiers in MATLAB

Section 29: 3.3: Clustering

Lecture 188 Code and Data

Section 30: 3.3.1: K-Means

Lecture 189 K-Means Clustering Intuition

Lecture 190 Choosing the number of clusters

Lecture 191 k-means in MATLAB (Part 1)

Lecture 192 k-means in MATLAB (Part 2)

Section 31: 3.3.2: Hierarchical Clustering

Lecture 193 Hierarchical Clustering Intuition (Part 1)

Lecture 194 Hierarchical Clustering in MATLAB

Lecture 195 Hierarchical Clustering Intuition (Part 2)

Section 32: 3.4: Dimensionality Reduction

Lecture 196 Code and data

Lecture 197 Principal Component Analysis

Lecture 198 PCA in MATLAB (Part 1)

Lecture 199 PCA in MATLAB (Part 2)

Section 33: 3.5: Project: Malware Analysis

Lecture 200 Code and data

Lecture 201 Problem Discription

Lecture 202 Customizing code templates for completing Task 1 and 2 (Part 1)

Lecture 203 Customizing code templates for completing Task 1 and 2 (Part 2)

Lecture 204 Customizing code templates for completing Task 3, 4 and 5

Lecture 205 Here is the project

Section 34: ––––––- Part 4: Data Preprocessing for Machine Learning using MATLAB ––-

Lecture 206 Introduction to course

Section 35: 4.1: Handling Missing Values

Lecture 207 Code and Data

Lecture 208 Deletion strategies

Lecture 209 Using mean and mode

Lecture 210 Considering as a special value

Lecture 211 Class specific mean and mode

Lecture 212 Random Value Imputation

Section 36: 4.2: Dealing with Categorical Variables

Lecture 213 Code and Data

Lecture 214 Categorical data with no order

Lecture 215 Categorical data with order

Lecture 216 Frequency based encoding4

Lecture 217 Target based encoding

Section 37: 4.3: Outlier Detection

Lecture 218 Code and Data

Lecture 219 3 sigma rule with deletion strategy

Lecture 220 3 sigma rule with filling strategy

Lecture 221 Box plots and iterquartile rule

Lecture 222 Class specific box plots

Lecture 223 Histograms for outliers

Lecture 224 Local Outlier Factor (Part 1)

Lecture 225 Local Outlier Factor (Part 2)

Lecture 226 Outliers in Categorical Variables

Section 38: 4.4: Feature Scaling and Data Discretization

Lecture 227 Code and Data

Lecture 228 Feature Scalling

Lecture 229 Discretization using Equal width binning

Lecture 230 Discretization using Equal Frequency binning

Section 39: 4.5: Project: Selecting the Right Method for your Data

Lecture 231 Code and Data

Lecture 232 Selecting the right method (Part 1)

Lecture 233 Selecting the right method (Part 2)

Section 40: ––––––- Part 5: Automate your Tasks using MATLAB –––

Lecture 234 Introduction to the course

Section 41: 5.1: Controlling Mouse and Keyboards to Automate Tasks

Lecture 235 Code and Data

Lecture 236 Writting to NotePad and then Deleting the Stuff

Lecture 237 Saving Files and Opening up Google Page

Lecture 238 Drawing a Tiger using Mouse and Keyboard

Section 42: 5.2: Emails, Web and Running Scripts from Command Window

Lecture 239 Code and Data

Lecture 240 Sending email, Opening a Webpage and Executing System Commands

Lecture 241 Automating Emails and other Tasks using Batch Files

Lecture 242 Automatic Screenshots and Sending them as Emails

Section 43: 5.3: Automatically Moving Deleting and Browsing Files

Lecture 243 Code and Data

Lecture 244 Automating Directory Interactions (Part 1)

Lecture 245 Automating Directory Interactions (Part 2)

Lecture 246 Finding files and arraning them in folder structures

Section 44: 5.4: Exceptions, assert, startup, finish, diary

Lecture 247 Code and Data

Lecture 248 Automating programs to work during errors

Lecture 249 Finish and Startup functions for loading preferences

Lecture 250 Automating program checking and logging

Section 45: 5.5: Automate user interactions

Lecture 251 Code and data

Lecture 252 Automating file interactions

Lecture 253 Automatic arrangment of pictures based on years

Lecture 254 Automate user interactions

Section 46: 5.6: Code debuggging and analyzer

Lecture 255 Code and Data

Lecture 256 Automate code inspection

Lecture 257 Common Errors

Section 47: 5.7: Textual processing for automatic summarization of contents

Lecture 258 Code and Data

Lecture 259 Summaring Textual Contents using Word Cloud

Lecture 260 Summaring Textual contents using topic models

Lecture 261 Read the html from a google search

Section 48: 5.8: Generating ppts, word documents and pdfs

Lecture 262 Code and Data

Lecture 263 Creating Presentations

Lecture 264 Adding Figures, Tables to Presentations

Lecture 265 Generating Word Documents

Lecture 266 Adding Figures and Tables to Word Documents

Section 49: –––––- Part 6: Regular Expressions using Matlab ––––––

Lecture 267 Introduction to the course

Section 50: 6.1: Introduction to Regular Expressions

Lecture 268 Codes

Lecture 269 Regular Expressions Fundamentals

Lecture 270 Executing Regular Expressions on Matlab, literals and meta characters

Lecture 271 Online Regex Engine

Lecture 272 The dot metacharacter

Section 51: 6.2: Character Classes

Lecture 273 Codes

Lecture 274 Basics of Character Classes

Lecture 275 Exclusion of characters using a character class

Lecture 276 Some exceptions with a character class

Lecture 277 Shorthand for character classes

Section 52: 6.3: Anchors and Word Boundaries

Lecture 278 Codes

Lecture 279 Staring and Ending Anchors

Lecture 280 Examples of Starting and Ending Anchors

Lecture 281 Word Boundaries (Part 1)

Lecture 282 Word Boundaries (Part 2)

Section 53: 6.4: Repetitiongs using Quantifiers

Lecture 283 Codes

Lecture 284 Quantifiers

Lecture 285 Limited Repetition

Lecture 286 Lazy and Greedy Quantifiers

Section 54: 6.5: Group Constructs

Lecture 287 Codes

Lecture 288 Understanding the Grouping

Lecture 289 Non-capturing groups

Lecture 290 Effect of Quantifiers on Groups

Lecture 291 Alternation

Lecture 292 Atomic Grouping

Section 55: 6.6: Assertions, Conditions and Backreferencing

Lecture 293 Codes

Lecture 294 Look Ahead Assertions

Lecture 295 Look Behind Assertions

Lecture 296 Backreferencing

Lecture 297 Named Capturing Groups and Backreferencing

Lecture 298 Conditions (if then else)

Lecture 299 Branch Reset

Section 56: 6.7: Practical Examples

Lecture 300 Codes

Lecture 301 Character Ranges

Lecture 302 Password Checking Example

Lecture 303 IP Addresses

Lecture 304 Matching a valid date

Section 57: –––––- Part 7: Matlab App Designing Using Guide ––––––

Lecture 305 Introduction to MATLAB Apps with Guide

Section 58: 7.1: Basics of the Guide

Lecture 306 Accessing Guide and the Available controls

Lecture 307 Properties of controls (Initial values and tags)

Lecture 308 Positioning and aligning controls

Lecture 309 Grid and lines

Lecture 310 Customizing tabbing behavior

Lecture 311 The created functions in the .m file

Lecture 312 The set and get functions

Section 59: 7.2: Linking the code with the GUI

Lecture 313 Codes

Lecture 314 GUI for a simple product program

Lecture 315 Including tables in GUI

Lecture 316 Working with the slider and including graphs

Lecture 317 Setting up a background image of a button

Lecture 318 Setting the menu

Lecture 319 Changing the backgrounds of a GUI

Lecture 320 Button group and radio buttons

Lecture 321 Using checkboxes

Lecture 322 Reading a file (text file) and displaying its contents

Lecture 323 Explaining toggle buttons

Lecture 324 pop up menu and list boxes

Lecture 325 hObject and Handles

Section 60: 7.3: Advance techniques for GUIDE

Lecture 326 Codes

Lecture 327 Passing values between GUI's

Lecture 328 Passing values between two call back functions

Lecture 329 How to pass command line arguments to the GUI

Section 61: 7.4: Sample projects with GUIDE

Lecture 330 Codes

Lecture 331 Sample project 1- Building a Calculator (Part 1)

Lecture 332 Sample Project 2: Image Processing (Part 1)

Lecture 333 Sample Project 2: Image Processing (Part 2)

Section 62: 7.5: More Useful Tricks and Examples with GUIDE

Lecture 334 Codes

Lecture 335 A trick with the visibility option of text box

Lecture 336 Simple string manipulation and user notification

Lecture 337 Deleting elements from a List box one by one programatically

Lecture 338 Adding elements to a list box programatically

Lecture 339 Selection Determination and Counter

Lecture 340 User notifications during processing with a push button

Lecture 341 Interacting with GUI from Keyboard

Lecture 342 Popup Menu Choice Restriction

Section 63: –––––- Part 8: Create MATLAB Apps with App Designer ––––––

Lecture 343 Introduction to MATLAB Apps with App Designer

Section 64: 8.1: Basics of AppDesigner

Lecture 344 Layout of the appdesigner

Lecture 345 Alignment and arranging options

Lecture 346 Spacing and resizing

Lecture 347 Grid Lines

Lecture 348 Error message for better coding

Lecture 349 Shortcuts for appdesigner

Section 65: 8.2: Coding GUI's

Lecture 350 Important notes before coding

Lecture 351 Simple addition program

Lecture 352 Slider and graphs

Lecture 353 label, text area and list boxes

Lecture 354 Drop down menu

Lecture 355 Radio buttons

Lecture 356 State buttons and spinner

Lecture 357 Switches and Textual Files

Lecture 358 Working with Tables

Lecture 359 Lamps and Tabs

Lecture 360 Guages and Knobs

Section 66: 8.3: Advance techniques

Lecture 361 Passing values between two call back functions

Lecture 362 Passing data between two GUI's

Lecture 363 Adding a custom built functions

Lecture 364 Background images nd calling multiple GUIs from script

Lecture 365 Packaging your app

Section 67: 8.4: Sample projects with App Designer

Lecture 366 Sample project 1: Building a calculator (Part 1)

Lecture 367 Sample Project 2: Image Processing

Section 68: BONUS: Discounted Coupons for my other MATLAB Courses

Lecture 368 Discounted coupons for MY other MATLAB courses

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