Udemy - 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