- 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
- Practical Data Science with MATLAB
- Overview of Data Processing and Feature Engineering
- Instructor Introduction
Exploratory Data Analysis
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
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
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
External Tool
- Create Datetime Variables
1
Videos
- Working with Dates and Times
1
Readings
- Practice Using Dates and Times
Combining Data
1
Discussions
- How many direct flights can you make?
3
Videos
- Importing Multiple Data Files
- Combining Data
- Joining Tables
Rearranging Data
1
Assignment
- Quiz 2: Organizing Your Data
2
Videos
- Sorting Your Data
- Summary of Module 2: Organizing Your Data
Missing Data
3
Videos
- Introduction to Module 3: Cleaning Your Data
- Identifying Missing Data
- Handling Missing Data
Outliers
2
Videos
- Identifying Outliers
- Investigating Outliers
1
Readings
- Practice Working with Outliers
Normalizing and Smoothing Data
1
External Tool
- Normalizing Data with z-scores
3
Videos
- Normalizing Data
- Examples of Normalizing Data
- Smoothing Data
Practice Cleaning Data
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
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
- Introduction to Unsupervised Learning
- Introduction to Clustering Algorithms
2
Readings
- Practice Clustering Data
- K-means Clustering
Feature Selection
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
- Introduction to Module 5: Domain-Specific Feature Engineering
- Feature Engineering Workflow
1
Readings
- Grading Information for Week 5
Processing Signals
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
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
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
- 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.

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