Video: .MP4, 1280×720 | Audio: AAC, 44 kHz, 2ch | Duration: 25h
Genre: eLearning | Language: English | Size: 10 GB
MATLAB from beginner to advance level with Advanced Data Types and Applications from Data Science and Data preprocessing
What you’ll learn
Develop beginer to advance level skills of Programming with MATLAB. This is the only course which enables you to learn intermediate and advance programming data structures such as structures, tables, times 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.
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
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