Machine Learning for Data Science using MATLAB!

Learn to implement classification and clustering algorithms using MATLAB with practical examples, projects and datasets!

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This course is for you if you want to learn Machine Learning techniques without having to learn all of the complicated math. Additionally, this course is also for you if you have had previous classes in machine learning theory but could never figure out how to implement and solve data science problems with it.

The approach in this course is very practical and we will start everything from scratch. We will immediately start coding after a couple of introductory tutorials and we will try to keep the theory to the bare minimum. All of the coding will be done in MATLAB, which is one of the fundamental programming languages for engineering and science students, and is frequently used by top data science research groups world wide.

Below is a brief outline of the course.

Segment 1: Introduction to Course

Segment 2: Data Preprocessing

Segment 3: Classification Algorithms in MATLAB

Segment 4: Clustering Algorithms in MATLAB

Segment 5: Dimensionality Reduction

Segment 6: Project: Malware Analysis


Your Instructor


Dr. Nouman Azam
Dr. Nouman Azam

Dr. Nouman Azam is an Assistant Professor in Computer Science. He teaches online courses related to MATLAB Programming to more than 10,000 students on different online platforms.

The focus in these courses is to explain different aspects of MATLAB and how to use them effectively in routine daily life activities. In my courses, you will find topics such as MATLAB programming, designing GUI's, data analysis and visualization.

Machine learning techniques using MATLAB is one of my favorite topics. During my research career I explore the use of MATLAB in implementing machine learning techniques such as bioinformatics, text summarization, text categorization, email filtering, malware analysis, recommender systems and medical decision making.


Course Curriculum


  Introduction to the Course and MATLAB
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  Data Preprocessing
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  Classification
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  K-Nearest Neighbor
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  Naive Bayes
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  Decision Trees
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  Support Vector Machines
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  Discriminant Analysis
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  Ensembles
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  Performance Evaluation
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  Clustering
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  K-Means
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  Hierarchical Clustering
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  Dimensionality Reduction
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  Project: Malware Analysis
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Frequently Asked Questions


When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

Get started now!