Predictive Modeling and Machine Learning with MATLAB

MathWorks via Coursera

Go to class Write review

Details

Go to class

Provider

Coursera
Pricing

Free Online Course (Audit)
Languages

English
Certificate

Paid Certificate Available
Duration & workload

22 hours 12 minutes
Sessions

On-Demand
Level

Intermediate
Subtitles

English, Arabic, French, Portuguese, German, Thai, Indonesian, Spanish, Kazakh, Hindi, Russian, Swedish, Korean, Greek, Italian, Chinese, Ukrainian, Japanese, Polish, Dutch, Turkish, Hungarian, Bengali, Pashto, Urdu, Azerbaijani, Farsi

Found in

Part of

Practical Data Science with MATLAB

4.8

Overview

Class Central Tips

In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB and Data Processing and Feature Engineering with MATLAB to increase your ability to harness the power of MATLAB to analyze data relevant to the work you do. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background. To be successful in this course, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation) and have completed courses 1 through 2 of this specialization. By the end of this course, you will use MATLAB to identify the best machine learning model for obtaining answers from your data. You will prepare your data, train a predictive model, evaluate and improve your model, and understand how to get the most out of your models.

Syllabus

Creating Regression Models

In this module you'll apply the skills gained from the first two courses in the specialization on a new dataset. You'll be introduced to the Supervised Machine Learning Workflow and learn key terms. You'll end the module by creating and evaluating regression machine learning models.

Creating Classification Models

In this module you'll learn the basics of classification models. You'll train several types of classification models and evaluation the results.

Applying the Supervised Machine Learning Workflow

In this module you'll apply the complete supervised machine learning workflow. You'll use validation data inform model creation. You'll apply different feature selection techniques to reduce model complexity. You'll create ensemble models and optimize hyperparameters. At the end of the module, you'll apply these concepts to a final project.

Advanced Topics and Next Steps

Taught by

Michael Reardon, Maria Gavilan-Alfonso, Erin Byrne, Matt Rich, Brandon Armstrong, Adam Filion, Isaac Bruss, Nikola Trica, Brian Buechel, Heather Gorr, and Sam Jones

Reviews

4.9 rating, based on 74 Class Central reviews

4.8 rating at Coursera based on 111 ratings

Start your review of Predictive Modeling and Machine Learning with MATLAB

Theophilus Kwofie

I had no experience with ML, but now I can boldly say that I can use ML to tackle real-world problems.
Magesh John

The course offered by MATHWORKS provides an excellent entry into the vast and ever-growing field of data science. The course starts with how we can visualise and clean data for better analyses before introducing you to unsupervised learning. Followi…

The course offered by MATHWORKS provides an excellent entry into the vast and ever-growing field of data science. The course starts with how we can visualise and clean data for better analyses before introducing you to unsupervised learning. Following unsupervised learning, the principle behind principal component analyses (PCA) is also explained in the best simplest way. The math behind it can be obtained, based on personal interest, from other resources. Then you are taken to supervised learning. The machine learning apps are the best what MATLAB offers which not only helps you create different models very fast and analyse but also generate the code behind it which can help you to later use code only for creating the model. It is only when you have the raw code you can do any kind of adjustments or modifications you may want.

The course is condensed. Please be prepared to code along with the the lectures. You may want to repeat it more than one time to really get an intuition of what is happening. The forums of discussion also provide excellent information and you may raise your queries there which are usually responded to promptly by the teaching staff.

The course clearly demonstrates the 'muscle power' MATLAB has in dealing with data. Backed up with the already vast arrays of built-in functions, you can wrangle and manipulate the data in any way you want.

To MATHWORKS teaching staff: a BIG THANK YOU from my side. Looking forward to more such courses. I may request you to provide the students with a pdf file of the course contents covering the major aspects taught in the course.
Masoud Fattahi Bandpey

The 'Predictive Modeling and Machine Learning with MATLAB' course offered a comprehensive dive into the nuances of MATLAB's machine learning toolbox. The real-world applications illustrated helped bridge the gap between theory and practice.
The instructors from MathWorks showcased a deep understanding of the subject, making even complex algorithms accessible for beginners.
I particularly appreciated the hands-on exercises and MATLAB code walkthroughs, which solidified my grasp of the topics.
Anonymous

II highly recommend the "Predictive Modeling and Machine Learning using MATLAB" course to anyone looking to gain a comprehensive understanding of machine learning techniques. Whether you're a beginner or looking to deepen your knowledge, this course provides a solid foundation and practical skills that are directly applicable to real-world projects. The investment in this course is undoubtedly worthwhile.
Anonymous

The course showcased a thorough comprehension of diverse model varieties and efficiently examined the dataset. The tutorials presented elaborate guidelines on using MATLAB tools efficiently. The program is excellently structured and includes assessments to evaluate the learners' grasp of the content. It's highly beneficial for individuals who are novices in the field of machine learning.
Zahra Nozarijouybari

Great course to interactively learn how to use Matlab Apps for Machine Learning Projects. Most of the assessments help to better understand the concepts and the pre-prepared live scripts and codes are very well-suited for getting one's hands into the work.
Anonymous

Hi
Predictive Modeling and Machine Learning with MATLAB provides a clear and practical approach, making complex concepts easily understandable. While beginner-friendly, those seeking advanced methodologies might find it introductory.
Anonymous

Great course for understanding the Machine learning workflow. Clear description of different techniques and delivering vital concepts of machine learning workflow
Christina Jacob

The course gave students a thorough understanding of the different types of models, allowed them to quickly explore the dataset, and showed them how predictors related to one another. The tutorials go into great detail on how to use MATLAB tools eff…

The course gave students a thorough understanding of the different types of models, allowed them to quickly explore the dataset, and showed them how predictors related to one another. The tutorials go into great detail on how to use MATLAB tools efficiently. The course is quite well-designed, and there are quizzes to assess the student's understanding of the material. Additionally, scripts of functions that can be used with our own datasets are provided. As a person from civil engineering plunging into this field was totally new but the classes were eye-opening for my research works. Looking forward to learning more courses from Coursera. It was a wonderful learning opportunity and offered a solid foundation for putting machine learning into practice.
Anonymous

A thorough comprehension of various model types, quick dataset analysis skills, and the capacity to identify correlations between predictors were all offered by the certification. The lectures provided detailed instructions for using the MATLAB tools as well as several illustrations. Excellent tests are provided in the course to gauge students' comprehension of the subject matter. Additional scripts of functions are provided, which we can apply with our own datasets. It was a fantastic learning experience and provided a strong foundation for the application of machine learning.
Additionally, the instructors have all the necessary skills for the course and are very knowledgeable about it.

Thanks!!
Anupam Sharma

It was one of the best course I took among many in search of proper course.
I can say this course and specialization it belongs to is having potential to make you ready for being a more than beginner level data scientist and gives you strong foundation upon which you can excel in any role where data science and machine learning is utilized.
I am big fan of Mathworks and MATLAB so if my review seems biased, "IT IS NOT."
Try the course and I am sure you will not be afraid to implement ML next time.
Just one thing - its will be good to have a 5/10 level programming skills before you start, and any language will do but OOPs concept should be somewhat you should be aware of.
Anonymous

The course demonstrated a comprehensive understanding of different model types, quickly exploring the dataset. The tutorials provide detailed information on how to use MATLAB tools effectively. The course is very well designed and there are tests to measure the student's understanding of the material. It is very helpful to people who are new to machine learning.
Anonymous

Very informative and well made presentations. The topic is quite interesting but often difficult to follow at other coursers or material. In this one the chaoters are well thought and the knowledge is provided in an intuitive way accompanied with graphs and pictures. Really good job Mathworks!
Shibbir Ahmed

This is one of the best courses I have taken on coursera. The course provides very clear examples, vivid visualisations, and rich videos to pinpoint the most important learning points. It gives access to Matlab online-which is really great to practice and learn faster.

The trainers are true experts in their field.

The course has great resources including very rich documentation.

This course can work as a reference guide for anyone who aspires to be a good data scientist. It helps build solid foundation in complex concepts in data science and machine learning.

Many thanks to the instructors of the course, and many thanks to MathWorks and coursera for such a great course!
Anonymous

This course is a great one to learn lots of machine learning techniques and apply them on true real life data. It has lots of deep technical content that definitely will help you advance your knowledge in ML smoothly!
Anonymous

It is very helpful. I have lots of questions and confusions before having this Course for Machine learning which Helps me a lot to understands things and get started to my own Project.
Ravi Chikkireddy

Hello,

I was a very pleasant experience. I never thought using ML algorithms is this easy. Thanks for making the material so interactive and effective. I practiced a lot. Enjoyed it.
Anonymous

Great course for predictive modeling and ML in MatLab. It might be useful for someone trying to learn ML despite MatLab, but is a course intended to be applicated using their tools.
Anonymous

That's one of the greatest courses in using ML on MATLAB, it seems that the course covers some advanced topics but everything is made so that the learners could progress easily throughout the course.

Just an advice for the future learners or for those who finished with the course, keep learning and if you're not familiar with the MATLAB Environment, i think taking courses on MATLAB fundamentals to experience more in depth strategies on how to use MATLAB in the future so that you could perform well on some very interesting big projects in the future.
Saba Siddiqui

The course provided the deep and quick insight into the types of models, to explore the dataset, and to see relationship between predictors in a little time. The videos are detailed about using the MATLAB tools effectively. The course is very well designed and has quiz exercises to evaluate the students' concepts and learning. Scripts of functions are also provided which can be applicable to our own datasets. It was a great learning experience and provided the good starting point for implementing the machine learning.