MATLAB Master Class: Go from Beginner to Expert in MATLAB

h264, yuv420p, 1280x720 |ENGLISH, 44100 Hz, 2 Channels | 36h 15mn | 14.52 GB







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Develop ber to advance level skills of Programming with MATLAB.







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



What you'll learn







This is the only course which enables you to learn intermediate and advance programming data structures such as structures, tables, s 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 a free trail copy of the software from the MATHWORK website. This is for limited 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 ing 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 eeering, 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 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 Ber to Advance







Snt 1.1: Handling variables and Creating Scripts







Snt 1.2: Doing Basic Maths in MATLAB







Snt 1.3: Operations on Matrices







Snt 1.4: Advance Math Functions with Symbolic Data Type







Snt 1.5: Interacting with MATLAB and Graphics







Snt 1.6: Importing Data into MATLAB







Snt 1.7: File Handling and Text Processing







Snt 1.8: MATLAB Programming







Snt 1.9: Sharing Your MATLAB Results







Part 2: Advance MATLAB Data Types







Snt 2.1: Cell Data Type







Snt 2.2: Tables and Tables







Snt 2.3: Working with Structures and Map Container Data Type







Snt 2.4: Converting between Different Data Types







Part 3: Machine Learning for Data Science Using MATLAB







Snt 3.1 Data Preprocessing







Snt 3.2. Classification







Snt 3.2.1 K-Nearest Neighbor







Snt 3.2.2 Naive Bayes







Snt 3.2.3 Decision Trees







Snt 3.2.4 Support Vector Machine







Snt 3.2.5 Discriminant Analysis







Snt 3.2.6 Ensembles







Snt 3.2.7 Performance Evaluation







Snt 3.3 Clustering







Snt 3.3.1 K-Means







Snt 3.3.2 Hierarchical Clu stering







Snt 3.4 Dimensionality Reduction







Snt 3.5 Project







Part 4: Data Preprocessing for Machine Learning using MATLAB







Snt 4.1 Handing Missing Values







Snt 4.2 Dealing with Categorical Variables







Snt 4.3 Outlier Detection







Snt 4.4 Feature Scaling and Data Discretization







Snt 4.5 Selecting the Right Method for your Data







Part 5: Build Regular Expression using MATLAB for Text Processing







Snt 5.1 : Introduction and getting started with regexes







Snt 5.2: Character Classes







Snt 5.3: Anchors and Word Boundaries







Snt 5.4: Repetitiongs using Quantifiers







Snt 5.5: Group Constructs







Snt 5.6: Assertions, Conditions and Backreferencing







Snt 5.7: Practical Examples







Part 6: Matlab App Designing Using Guide







Snt 6.1: Basics of the GUIDE







Snt 6.2: Linking the Code with GUI







Snt 6.3: Advance Techniques for GUIDE







Snt 6.4: Sample Projects with GUIDE







Snt 6.5: More Useful Tricks and Examples with GUIDE







Part 7: Create MATLAB Apps with App Designer







Snt 7.1: Basics of App Designer







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







Snt 7.3: Coding GUI's







Snt 7.4: Advance Techniques







Snt 7.5: Sample Projects with App Designer







Who this course is for:







Anyone looking to build a strong career in science or eeering through Excellent MATLAB coding skills







Anyone wanting to advance their skills of real world problem solving with MATLAB based scientific computing