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Data Processing and Feature Engineering with MATLAB
  • Level Professional
  • المدة 20 ساعات hours
  • الطبع بواسطة MathWorks
  • Offered by

عن

In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB to lay the foundation required for predictive modeling. This intermediate-level course is useful to anyone who needs to combine data from multiple sources or times and has an interest in modeling. 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 Exploratory Data Analysis with MATLAB. Throughout the course, you will merge data from different data sets and handle common scenarios, such as missing data. In the last module of the course, you will explore special techniques for handling textual, audio, and image data, which are common in data science and more advanced modeling. By the end of this course, you will learn how to visualize your data, clean it up and arrange it for analysis, and identify the qualities necessary to answer your questions. You will be able to visualize the distribution of your data and use visual inspection to address artifacts that affect accurate modeling.

الوحدات

Welcome to the Course

    • 3 Videos
Show info about module content

3 Videos

  • Practical Data Science with MATLAB
  • Overview of Data Processing and Feature Engineering
  • Instructor Introduction

Exploratory Data Analysis

    • 3 Videos
    • 3 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Understanding the Flights Dataset

1 Discussions

  • Feeling unlucky with delays?

3 Videos

  • Introduction to Module 1
  • Introduction to the Flights Dataset
  • Exploring the Flights Dataset

3 Readings

  • Access MATLAB
  • Data and Code Files
  • Variables in the Flights Dataset

Introduction to Distributions

    • 4 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 1 Quiz

4 Videos

  • Describing Distributions
  • Examples of Distributions
  • Visualizing Multidimensional Data
  • Summary of Module 1: Surveying Your Data

1 Readings

  • Practice Visualizing Multidimensional Data

Working with Text

    • 2 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Practice Working with Strings

2 Videos

  • Introduction to Module 2: Organizing Your Data
  • Working with Strings

1 Readings

  • Practice Working with Strings

Working with Dates and Times

    • 1 Videos
    • 1 Readings
    • 1 ExternalTool
Show info about module content

1 External Tool

  • Create Datetime Variables

1 Videos

  • Working with Dates and Times

1 Readings

  • Practice Using Dates and Times

Combining Data

    • 3 Videos
    • 1 Discussion
Show info about module content

1 Discussions

  • How many direct flights can you make?

3 Videos

  • Importing Multiple Data Files
  • Combining Data
  • Joining Tables

Rearranging Data

    • 2 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Quiz 2: Organizing Your Data

2 Videos

  • Sorting Your Data
  • Summary of Module 2: Organizing Your Data

Missing Data

    • 3 Videos
Show info about module content

3 Videos

  • Introduction to Module 3: Cleaning Your Data
  • Identifying Missing Data
  • Handling Missing Data

Outliers

    • 2 Videos
    • 1 Readings
Show info about module content

2 Videos

  • Identifying Outliers
  • Investigating Outliers

1 Readings

  • Practice Working with Outliers

Normalizing and Smoothing Data

    • 3 Videos
    • 1 ExternalTool
Show info about module content

1 External Tool

  • Normalizing Data with z-scores

3 Videos

  • Normalizing Data
  • Examples of Normalizing Data
  • Smoothing Data

Practice Cleaning Data

    • 1 Videos
    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Practice Quiz: Putting it all Together
  • Quiz 3: Cleaning Your Data

1 Videos

  • Summary of Module 3: Cleaning Your Data

1 Readings

  • Cleaning Data: Analyzing Flight Volume

Feature Engineering

    • 2 Videos
    • 1 Readings
    • 1 ExternalTool
Show info about module content

1 External Tool

  • Feature Generation Through Discretization

2 Videos

  • Introduction to Module 4: Finding Features that Matter
  • Introduction to Feature Engineering

1 Readings

  • Examples of Feature Engineering

Unsupervised Learning

    • 2 Videos
    • 2 Readings
Show info about module content

2 Videos

  • Introduction to Unsupervised Learning
  • Introduction to Clustering Algorithms

2 Readings

  • Practice Clustering Data
  • K-means Clustering

Feature Selection

    • 3 Videos
    • 2 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Quiz 4: Finding Features that Matter

1 Discussions

  • How many features does your data have?

3 Videos

  • Evaluating Features
  • Introduction to Dimensionality Reduction and PCA
  • Summary of Module 4: Finding Features that Matter

2 Readings

  • Applying Filter Methods
  • Applying PCA

Getting Started

    • 2 Videos
    • 1 Readings
Show info about module content

2 Videos

  • Introduction to Module 5: Domain-Specific Feature Engineering
  • Feature Engineering Workflow

1 Readings

  • Grading Information for Week 5

Processing Signals

    • 4 Videos
    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Practice Finding Peaks
  • Signal Processing Graded Quiz

4 Videos

  • Synchronizing Data with Timetables
  • Summary Statistics as Features
  • Finding Peaks
  • Optional: Recording Sensor Data with MATLAB Mobile

1 Readings

  • Practice using Summary Stats as Features

Processing Images

    • 1 Videos
    • 1 Readings
    • 1 Discussion
    • 1 ExternalTool
    • 1 Assignment
Show info about module content

1 Assignment

  • Image Processing Graded Quiz

1 External Tool

  • Practice Segmenting Images

1 Discussions

  • What other features could you use?

1 Videos

  • Feature Engineering and Clustering with Images

1 Readings

  • Practice Working with Images

Processing Text

    • 2 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Text Processing Graded Quiz

2 Videos

  • Feature Engineering with Text
  • Feature Engineering with Storm Events

1 Readings

  • Modeling Using Qualitative Descriptions

Wrap-up

    • 2 Videos
    • 1 Readings
Show info about module content

2 Videos

  • Summary of Module 5: Domain-Specific Feature Engineering
  • Summary of Data Processing and Feature Engineering

1 Readings

  • Provide Feedback on Your Course Experience

Auto Summary

Enhance your data science skills with the "Data Processing and Feature Engineering with MATLAB" course, designed for intermediate learners who aim to advance their predictive modeling capabilities. Offered by Coursera, this course is ideal for individuals with domain knowledge and some exposure to computational tools, even if they lack a programming background. Participants should have a basic understanding of statistics and are encouraged to complete the "Exploratory Data Analysis with MATLAB" course beforehand. Over the duration of 1200 minutes, learners will acquire the necessary skills to merge data from various sources, tackle common issues like missing data, and apply specialized techniques for handling textual, audio, and image data. By the course's conclusion, you will be proficient in visualizing, cleaning, and organizing data for analysis, as well as identifying key data attributes for accurate modeling. The course offers flexible subscription options, including Starter, Professional, and Paid plans, catering to a diverse audience aiming to refine their data science expertise. Join today to transform your data processing and feature engineering skills with MATLAB.

Michael Reardon
Instructors

Michael Reardon

Maria Gavilan-Alfonso
Instructors

Maria Gavilan-Alfonso

Erin Byrne
Instructors

Erin Byrne

Cris LaPierre
Instructors

Cris LaPierre

Matt Rich
Instructors

Matt Rich

Brandon Armstrong
Instructors

Brandon Armstrong

Adam Filion
Instructors

Adam Filion

Nikola Trica
Instructors

Nikola Trica

Isaac Bruss
Instructors

Isaac Bruss

Brian Buechel
Instructors

Brian Buechel

Heather Gorr
Instructors

Heather Gorr