MATLAB Master Class: Go from Beginner to Expert in MATLAB
Free Coupon Discount - MATLAB Master Class: Go from Beginner to Expert in MATLAB, MATLAB from beginner to advance level with Advanced Data Types and Applications from Data Science and Data preprocessing
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Created by Nouman Azam
English [Auto]00
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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. 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 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
Part 5: Build Regular Expression using MATLAB for Text Processing
Segment 5.1 : Introduction and getting started with regexes
Segment 5.2: Character Classes
Segment 5.3: Anchors and Word Boundaries
Segment 5.4: Repetitiongs using Quantifiers
Segment 5.5: Group Constructs
Segment 5.6: Assertions, Conditions and Backreferencing
Segment 5.7: Practical Examples
Part 6: Matlab App Designing Using Guide
Segment 6.1: Basics of the GUIDE
Segment 6.2: Linking the Code with GUI
Segment 6.3: Advance Techniques for GUIDE
Segment 6.4: Sample Projects with GUIDE
Segment 6.5: More Useful Tricks and Examples with GUIDE
Part 7: Create MATLAB Apps with App Designer
Segment 7.1: Basics of App Designer
Segment 7.2: Tips and Tricks for Effective use of App Designer
Segment 7.3: Coding GUI's
Segment 7.4: Advance Techniques
Segment 7.5: Sample Projects with App Designer
100% Off Udemy Coupon . Free Udemy Courses . Online Classes
Bestseller
Created by Nouman Azam
English [Auto]00
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Preview this Udemy Course GET COUPON CODE
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. 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 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
Part 5: Build Regular Expression using MATLAB for Text Processing
Segment 5.1 : Introduction and getting started with regexes
Segment 5.2: Character Classes
Segment 5.3: Anchors and Word Boundaries
Segment 5.4: Repetitiongs using Quantifiers
Segment 5.5: Group Constructs
Segment 5.6: Assertions, Conditions and Backreferencing
Segment 5.7: Practical Examples
Part 6: Matlab App Designing Using Guide
Segment 6.1: Basics of the GUIDE
Segment 6.2: Linking the Code with GUI
Segment 6.3: Advance Techniques for GUIDE
Segment 6.4: Sample Projects with GUIDE
Segment 6.5: More Useful Tricks and Examples with GUIDE
Part 7: Create MATLAB Apps with App Designer
Segment 7.1: Basics of App Designer
Segment 7.2: Tips and Tricks for Effective use of App Designer
Segment 7.3: Coding GUI's
Segment 7.4: Advance Techniques
Segment 7.5: Sample Projects with App Designer
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