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Predictive Modeling and Machine Learning with MATLAB

MathWorks via Coursera


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.


  • 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

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4.7 rating, based on 26 reviews

Start your review of Predictive Modeling and Machine Learning with MATLAB

  • 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
    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
  • Profile image for Parv Khandelwal
    Parv Khandelwal
    For the ones who want to learn predictive modeling under data science machine learning, this is a really great course to start with!!! In detail description of how to use matlab and also side by side practical questions so that you keep practicing and keep getting better at it. By the end of it you will be able to understand and perform predictive modeling in a fairly good manner!
  • Anonymous
    Would rate 4.5, fantastic course with a lot to learn. I just felt like certain topics, particularly the code for some procedures felt rushed.

    As a result I wasn't comfortable with certain topics, such as exploring metrics which might indicate overfitting.

    Suggested improvements would be more hands on exercises in addition to the live scripts.
  • Anonymous
    The content of course was pretty amazing. The guide described important parameter for creating a model, how to enhance the model performance, what are the parameter while considering the model for prediction.

    The course was very knowledgeable. The videos were explaining the workflow. Thank You very much
  • Anonymous
    It's the perfect course for anyone who wants to perform machine learning in the real world.

    I believe I couldn't learn machine learning without this course. It's challenging to understand machine learning in-depth. Still, I learned about all the models in this course motivated me to study further.
  • Profile image for Rakibul Hassan Rana
    Rakibul Hassan Rana
    Thanks a lot, Coursera and Mathworks, for arranging the awesome course Data Science with MATLAB Specialization. All aspects of the courses are really excellent and fully practical approaching oriented. This will help me a lot to build up my career and help to reach my career goal.
  • Anonymous
    It is a good comprehensive course. It explains the concepts behind the ML technology as well as integrates the use of MATLAB as a tool to effectively consolidate the learning.
    Very helpful for a Python driven ML person to explore the power and data visualization excellence of Matlab.
  • Anonymous
    An excellent introduction to machine learning however the level of MATLAB proficiency was very high for only the third course in the specialization. As with the other courses the pace of the videos was way too fast to keep up requiring multiple viewings just to keep pace.
  • Anonymous
    The course was very profound and focused on the most key aspects of machine learning application. The walkthrough and the provided learning materials in the form of live scripts made it very much easier to grasp the concepts and apply them at the same time using Matlab.
  • Anonymous
    This course is definitely useful! From the basics to the most advanced machine learning techniques. However, I would strongly recommend to attend some specific courses about machine learning before attendind the last course of this specialization.
  • Anonymous
    Great course. Learned the basics but some theory was only briefly discussed. Quizzes and exercises are very useful to apply the knowledge presented. Some videos were quite condensed but capture the basics well after reviewing again.
  • Anonymous
    Great course, the examples are interesting and the methods are taught in a broad way, so that it is easy to understand how to apply them to other sets of data with different characteristics. Looking forward to the last module
  • Anonymous
    Thank you MATLAB team, Great work. I learned a lot from this course, especially handling class imbalance, tuning hyperparameters, and misclassification. I would recommend this course to all fresh data scientists.
  • Anonymous
    I really like it and learn too much thank you .. really dealing with Matlab is a challenge so I recommend taking this course and do more courses in the Matlab basic.
  • Anonymous
    Great course structures and workflows. It helps me a lot in applying the knowledge I gained from the first two courses in machine learning projects. Thank you.
  • Profile image for Alexey Nosov
    Alexey Nosov
    I liked the course. It touches on the very latest in data science and machine learning, is perfectly organized, and I got answers to many of my questions.
  • Profile image for Mizanur Rahman Mizan
    Mizanur Rahman Mizan
    Excellent Course. The practical approach made the courses themselves unique and interesting. This specialization will make a learner skill in the domain.
  • Anonymous
    Great course, indeed. It's well-organized, well-designed and quite useful for learning machine learning workflow and algorithms with practical approaches.
  • Anonymous
    It was clear, complet, well designed. The materials are of high quality. The exercises are useful and helpful. I highly recommend this course.

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