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Data Science Project: MATLAB for the Real World

MathWorks via Coursera


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Like most subjects, practice makes perfect in Data Science. In the capstone project, you will apply the skills learned across courses in the Practical Data Science with MATLAB specialization to explore, process, analyze, and model data. You will choose your own pathway to answer key questions with the provided data. To complete the project, you must have mastery of the skills covered in other courses in the specialization. The project will test your ability to import and explore your data, prepare the data for analysis, train a predictive model, evaluate and improve your model, and communicate your results.


  • Import and Explore the Data
    • In this module you'll be introduced to the goals of the capstone project. You will complete the initial task of preparing a data set and performing an exploratory analysis.
  • Create and Evaluate Features
    • In this module you'll perform feature engineering. You'll create a response variable and investigate the relationships between features and the response variable.
  • Apply Machine Learning
    • In this module you will perform machine learning. You'll train and customize various models. Using validation data and common evaluation metrics you'll choose the most appropriate model for the problem.
  • Communicate Your Results
    • In this module, you'll learn a framework for creating a data science story and the importance of crafting your narrative for the intended audience, along with tips for creating meaningful visualizations.

Taught by

Michael Reardon, Brandon Armstrong, Erin Byrne, Adam Filion, Heather Gorr, Maria Gavilan-Alfonso, Matt Rich, and Isaac Bruss


4.8 rating at Coursera based on 24 ratings

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