MATLAB Master Class Go from Beginner to Expert in MATLAB

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.



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

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



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



Last updated 7/2019