MATLAB matrix laboratory is a major and leading programming tools used by engineers, scientists, IT professionals, etc. It is a must-learn skill for anyone who wants to develop a career in engineering, IT Professionals, or related fields. Learning MATLAB can boost up your career.
This course is designed from the perspective of a student who has no prior knowledge of MATLAB. The time starts from the fundamental concepts and then built on top of those basic concepts and moves towards more advanced topics such as visualization, exporting and importing data, advanced data types and data structures, and advanced 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 divided into four different parts. Below is the detailed outline of this course.
Module 1 : MATLAB from Beginner to Advanced
- Ep 1.1: Handling variables and Creating Scripts
- Ep 1.2: Doing Basic Maths in MATLAB
- Ep 1.3: Operations on Matrices
- Ep 1.4: Advance Math Functions with Symbolic Data Type
- Ep 1.5: Interacting with MATLAB and Graphics
- Ep 1.6: Importing Data into MATLAB
- Ep 1.7: File Handling and Text Processing
- Ep 1.8: MATLAB Programming
- Ep 1.9: Sharing Your MATLAB Results
Module 2: Advance MATLAB Data Types
- Ep 2.1: Cell Data Type
- Ep 2.2: Tables and Time Tables
- Ep 2.3: Working with Structures and Map Container Data Type
- Ep 2.4: Converting between Different Data Types
Module 3: Machine Learning for Data Science Using MATLAB
- Ep 3.1 Data Preprocessing
- Ep 3.2. Classification
- Ep 3.2.1 K-Nearest Neighbor
- Ep 3.2.2 Naive Bayes
- Ep 3.2.3 Decision Trees
- Ep 3.2.4 Support Vector Machine
- Ep3.2.5 Discriminant Analysis
- Ep 3.2.6 Ensembles
- Ep 3.2.7 Performance Evaluation
- Ep 3.3 Clustering
- Ep 3.3.1 K-Means
- Ep 3.3.2 Hierarchical Clustering
- Ep 3.4 Dimensionality Reduction
- Ep 3.5 Project
Module 4: Data Preprocessing for Machine Learning using MATLAB
- Ep 4.1 Handling Missing Values
- Ep 4.2 Dealing with Categorical Variables
- Ep 4.3 Outlier Detection
- Ep 4.4 Feature Scaling and Data Discretization
- Ep4.5 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
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 to run the commands and scripts that we cover during the course period. If you do not have the MATLAB software installed, then you may consider the following options.
- You may download a free trial copy of the software from the MATH WORK website). It is for limited time use
- If you are a student or employee, you may contact your school or employer for a free copy. Many universities offer a free student version of the software
- You may consider downloading the Octave, which is free and has nearly identical functionality as 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)
- If none of the above works for you, then you may purchase the student version directly from the Mathworks website, which is significantly lower in cost compared to its full version