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.
Ce cours fait partie de la Spécialisation Practical Data Science with MATLAB
Data Processing and Feature Engineering with MATLAB
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À propos de ce cours
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Feature EngineeringMatlabData Cleansing
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Niveau intermédiaire
Approx. 26 heures pour terminer
Recommandé : 12 hours/week
Anglais
Sous-titres : Anglais
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MathWorks
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Programme du cours : ce que vous apprendrez dans ce cours
3 heures pour terminer
Surveying Your Data
In this module you'll apply the skills gained in Exploratory Data Analysis with MATLAB on a new dataset. You'll explore different types of distributions and calculate quantities like the skewness and interquartile range. You'll also learn about more types of plots for visualizing multi-dimensional data.
3 heures pour terminer
10 vidéos (Total 46 min), 4 lectures, 2 quiz
10 vidéos
Overview of Data Processing and Feature Engineering3 min
Instructor Introduction2 min
Introduction to Module 11 min
Introduction to the Flights Dataset7 min
Exploring the Flights Dataset5 min
Describing Distributions6 min
Examples of Distributions5 min
Visualizing Multi-Dimensional Data8 min
Summary of Module 1: Surveying Your Data2 min
4 lectures
Download and Install MATLAB15 min
Data and Code Files15 min
Variables in the Flights Dataset15 min
Practice Visualizing Multidimensional Data45 min
2 exercices pour s'entraîner
Understanding the Flights Dataset20 min
Module 1 Quiz30 min
3 heures pour terminer
Organizing Your Data
In this module you'll learn to prepare data for analysis. Often data is not recorded as required. You'll learn to manipulate string variables to extract key information. You'll create a single datetime variable from date and time information spread across multiple columns in a table. You'll efficiently load and combine data from multiple files to create a final table for analysis.
3 heures pour terminer
8 vidéos (Total 34 min), 2 lectures, 3 quiz
8 vidéos
Working with Strings7 min
Working with Dates and Times4 min
Importing Multiple Data Files4 min
Combining Data5 min
Joining Tables5 min
Sorting Your Data3 min
Summary of Module 2: Organizing Your Data2 min
2 lectures
Practice Working with Strings15 min
Practice Using Dates and Times30 min
2 exercices pour s'entraîner
Practice Working with Strings15 min
Quiz 2: Organizing Your Data1 h
3 heures pour terminer
Cleaning Your Data
In this module you'll clean messy data. Missing data, outliers, and variables with very different scales can obscure trends in the data. You'll find and address missing data and outliers in a data set. You'll compare variables with different scales by normalizing variables.
3 heures pour terminer
9 vidéos (Total 44 min), 2 lectures, 3 quiz
9 vidéos
Identifying Missing Data6 min
Handling Missing Data5 min
Identifying Outliers5 min
Investigating Outliers6 min
Normalizing Data4 min
Examples of Normalizing Data4 min
Smoothing Data7 min
Summary of Module 3: Cleaning Your Data1 min
2 lectures
Practice Working with Outliers1 h
Cleaning Data: Analyzing Flight Volume30 min
2 exercices pour s'entraîner
Practice Quiz: Putting it all Together15 min
Quiz 3: Cleaning Your Data40 min
4 heures pour terminer
Finding Features that Matter
In this module you'll create new features to better understand your data. You'll evaluate features to determine if a feature is potentially useful for making predictions.
4 heures pour terminer
7 vidéos (Total 35 min), 4 lectures, 2 quiz
7 vidéos
Introduction to Feature Engineering5 min
Introduction to Unsupervised Learning3 min
Introduction to Clustering Algorithms6 min
Evaluating Features8 min
Introduction to Dimensionality Reduction and PCA5 min
Summary of Module 4: Finding Features that Matter1 min
4 lectures
Examples of Feature Engineering30 min
Example of K-means Clustering15 min
Applying Filter Methods30 min
Applying PCA45 min
1 exercice pour s'entraîner
Quiz 4: Finding Features that Matter45 min
Avis
4.9
Meilleurs avis pour DATA PROCESSING AND FEATURE ENGINEERING WITH MATLAB
par SKMar 14, 2020
Highly recommended for people with patience, and deep interest in Data Processing and Feature Engineering. It is not easy. However, MATLAB instructional tools make this process so much simplified!
par SEFeb 25, 2020
The course content and delivery are top-notch. I like the practicals, quizzes and exams which help to deepen understanding. For me, they'll always be a treasure load of reference materials.
par DFeb 7, 2020
Overall I will rate it 9/10 which is really good. Only downside for me is that it was really fast, not enough interactive assignments and sometimes difficult to follow
par VAMar 9, 2020
The course is good and very well structured. It helps you understand the steps involved in feature engineering and provides proper ways to implement them in MATLAB.
par KSFeb 18, 2020
Fun (and easy) with the nice addition of playing with the Matlab functions yourself thanks to the temporary toolbox licenses.
par ORMar 5, 2020
I wish if I can give you more than five stars, Thank you for this amazing course.
par IAMar 16, 2020
The overall content was good. Quizzes could be more independent and technical.
par FMFeb 16, 2020
It provides a lot of insight about different tasks Matlab can do for you
par IMMar 4, 2020
Top course, amazingly explained and with high-valuable examples
À propos du Spécialisation Practical Data Science with MATLAB
Do you find yourself in an industry or field that increasingly uses data to answer questions? Are you working with an overwhelming amount of data and need to make sense of it? Do you want to avoid becoming a full-time software developer or statistician to do meaningful tasks with your data?
Completing this specialization will give you the skills and confidence you need to achieve practical results in Data Science quickly. Being able to visualize, analyze, and model data are some of the most in-demand career skills from fields ranging from healthcare, to the auto industry, to tech startups.
This specialization assumes you have domain expertise in a technical field and some exposure to computational tools, such as spreadsheets. To be successful in completing the courses, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation).
Throughout this specialization, you will be using MATLAB. MATLAB is the go-to choice for millions of people working in engineering and science, and provides the capabilities you need to accomplish your data science tasks. You will be provided with free access to MATLAB for the duration of the specialization to complete your work.
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
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