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Coursera

Predictive Modeling and Machine Learning with MATLAB

MathWorks via Coursera

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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

Reviews

4.8 rating, based on 53 Class Central reviews

4.8 rating at Coursera based on 103 ratings

Start your review of Predictive Modeling and Machine Learning with MATLAB

  • 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. Following...
  • 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!
  • Profile image for Saba Siddiqui
    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.
  • Anonymous
    This course very effectively build on what was taught in the first two courses of this series: 1-Exploratory Data Analysis and 2-Data Processing and Feature Engineering. It is considerably more rigorous than the first two courses, however, the extra time and effort to complete this course was more than worth the time. I feel I am much better prepared to tackle my own data analysis and preparation tasks.
  • Anonymous
    The course seemed quite good to me, it allows me to enter the subject in a didactic and fast way.
    MATLAB turns out to be a very good tool for working with data. I note that to take this course it is necessary to have the data processing course.
  • Anonymous
    The course is well-organized and well-adaptable to many fields of knowledge. A student will surely learn a lot by taking this course (and the whole MatLab specialization).
  • Anonymous
    What a beautiful course with amazing content and explanation. It helped me to revise my concepts and get a new perspective. Kudos to Mathworkers who are part of this!!
  • Profile image for Suresh Bishnoi
    Suresh Bishnoi
    This course is very helpful to understand machine learning and apply it through MATLAB which will also be helpful to apply the same concept through another platform.
  • Anonymous
    It is in fact a good course and comprehensive one. I learned a lot from this course. I practiced a lot that made my concepts clear about regression and classification.
  • 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.
  • Anonymous
    The most in-depth course in this specialization so far. A great deal of material was covered and like in the second course, dealing with MATLAB is a bit challenging. Participants really need more knowledge basic MATLAB to tackle the programming in most of the quizzes and exercises. I just felt like the code for some procedures was rushed, with the instructor assuming the student knew the subtle details of every command used.

    The reading’s presented as livescipts really need to be converted to video presentations because I was left feeling like I missed something.

    Any and all of my questions were promptly addressed in the Discussion forums.

  • Anonymous
    It was a great experience for me, it was so helpful and I learned a lot of new things. I highly recommend it for whoever is interested in this topic its so helpful and well organized.
  • Anonymous
    This is an excellent course, I really enjoyed it and I learned a lot of good things. Thanks a lot to the teachers, you are just amazing. God bless you.
  • Anonymous
    Love these introductory courses to ML and Feature engineering. I think the entire specialization is a great kick start for your data science carreer.
  • Anonymous
    I didn't think I would have a good enough grasp on Machine Learning from this course as all other online resources have found were really complicated and require some background knowledge. This course was simple to understand and I feel confident with the material covered. The quizzes are excellent ways for the learner to grasp the material covered in the videos and the live scripts make interacting with the matlab code enjoyable compared to online machine learning code repositories which are not as detailed and are more complicated
  • Anonymous
    Excellent course. It is very recommended as starting point for ML.................................................................
  • Shreeder Adibhatla
    Really good overview and summary of key machine learning concepts, including the Ml workflow (nice block diagram that summarizes it), feature selection, model optimization, oversampling and undersampling, and autoML. There are also a lot of Matlab commands and functions that you pick up as part of the worked out examples provided in the .mlx notebook files -- while this means that you don't figure a way to do it yourself (it would make the course too hard), they can be used as reference material in the future.
  • Anonymous
    It was really helpful to build my project. My project is related to classification so it was really helped me lot
  • Anonymous
    Excellent course. All the videos and exercises are very well organize making a great experience to learn.
  • Anonymous
    The course is very complete and provides all you need for rapid applicability. I would add two suggestions:

    Add some more mathematical implications and interpretation of the models used. You already do some of it but In my opinion, it remains a little simplistic.

    I think it would be better to assess the completion of some readings (for example live scripts in the modules) by means of additional quizzes.
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