MATLAB: From absolute scratch to the top!

Learning to ''think as a machine''

4.83 (3 reviews)
Udemy
platform
English
language
Other
category
33
students
9 hours
content
Sep 2021
last update
$19.99
regular price

What you will learn

Matlab programming

Matlab

Matlab applications

Differential equations solving via Matlab

Matlab and API programming

Curve Fitting

Description

Programming is ''TALKING'' to a machine in order to let it know what do we want and expect which requires a specific SINTAXIS. Most students get frustrated from not understanding programming because most systems out there do not stop to explain how machines work and ''THINK''. And I know what you are thinking: Machines do not think, do they? Actually no, but they are very ''dumb'' to do things that we take for granted, like counting from 1 to 10, for example. Only by understanding the ins and outs of what is happening inside the ''BRAINS'' of a computer (i.e. how it ''THINKS'') will we be able to adequately ''TALK'' to them. Every concept in this course will be explained and practiced with an example so that we see how the machine is reading what we are telling it to do. By knowing how the machine ''READ'' and interpreted your instructions, SINTAXIS will come as second nature, and you won't need to learn it by memory as you will have understood it.


This course will arm you with everything you need to know to be able to use MATLAB in your college and professional career by the end of it so you can let Matlab be your helpful ally in any kind of statistical, mathematical, engineering or logical task that needs a computer solution.


At the beggining of every module, we will see the exact results of our practical project so that we aim all the concepts that we learn towards it, thus, we will see each and every tool with a goal in mind.

Content

Module 0 (Introduction)

Intro
What to expect?
What is matlab and why is it so powerful and useful?

Module 1 (the environment, the fundamental commands and our first application)

Final project presentation
The programming environment
The semicolon
Space separation
Order of precedence in Matlab calculations
Scripts
Matlab is a case sensitive programming language
Read your errors
Functions
Comments
Variable types and matrix declarations
Global and local variables
The input and disp commands
The switch case statement
Module's final project

Thinking as a machine, the discrete world and iterative processes (The FOR loop)

Final project (and mini project) presentation
Thinking as a machine part I
Thinking as a machine part II
Introducing the For Loop
For Loop (counting steps other than 1)
Mini project: Calculating the compound interest
The Riemann sum (numerical integration) Part I: The definitions
The Riemann sum (numerical integration) Part II: Case study and application
The Riemann sum (numerical integration) Part III: For within a For
Orange warnings
Plot numbering and tittles, axis labeling and the grid on command
Saving plots as images (do not screen capture them)
The Trapezoid rule (numerical integration) Part I: The definitions
The Trapezoid rule (numerical integration) Part II: Trapezoid Rule vs Riemann
The Trapezoid rule and the Riemann sum by using MATLAB prebuilt functions

Thinking as a machine: The WHILE statement and the Newton-Rhapson method

Final project presentation
The theory behind the While Loop (a comparison against the For Loop) Part I
The theory behind the While Loop (a comparison against the For Loop) Part II
The theory behind the While Loop (a comparison against the For Loop) Part III
The Newton-Raphson numerical method
Handles (a little parenthesis before we practice Newton-Raphson)
Newton-Raphson method (practical lecture)
Module's final project: Newton-Raphson within a while loop (Part I)
Module's final project: Newton-Raphson within a while loop (Part II)
Module's final project: Newton-Raphson within a while loop (Bonus Part)
fzero function
fsolve function

The IF - ELSE statement

Introducing the IF statement
Primality test (The IF statement within a while loop and the break command)
Final project presentation
Gauss-Jordan theoretical lecture
Basic operations with matrixes
Gauss-Jordan implementation part I
Gauss-Jordan implementation part II
Gauss-Jordan implementation part III
Gauss-Jordan implementation part IV
Gauss-Jordan implementation part V
Gauss-Jordan implementation part VI
Gauss-Jordan implementation part VII
Gauss-Jordan implementation part VIII
Linsolve function

The TRY - CATCH statement

Introducing the final project
What is an API and introducing the try catch statments
Creating an account on weatherstack
Reviewing the API documentation
Making the API requests within a TRY statement
Parsing structure type variables
Wrapping up the final details of our API requests function
A little clarification before we move on to the next module

Curve fitting

Introducing the final project
Curve fitting theory
Loading the data
fminunc and getting the best curve fit
Calculating the R square for our curve fitting process
Curve fitting a parabola
The Polyfit function and the curve fitting app

First order Ordinary Differential Equations (first order ODEs)

Introducing the final project
Introducing symbolic type variables.
Using dsolve to solve differential equations via symbolic variables
Solving differential equations via dsolve and subs.
Using dsolve and subs within a function
Introducing the Eurler's Method
First Euler's method application on Series RL circuit
Eulers method vs analitical method
ode45 comparison

Greater order Ordinary Differential Equations

Final project presentation
Basic theoretical concepts for solving system of ordinary differential equations
Using dsolve and subs for system of differential equations Part II
Using ode45 for system of differential equations PART II
Writing a script to solve a series RLC circuit bot numerically and symbolically
Playing around with our script

Congratulations

Final class

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1842268
udemy ID
8/6/2018
course created date
7/14/2021
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