This course is part of the Practical Data Science with MATLAB Specialization

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Michael Reardon +10 more instructors

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Practical Data Science with MATLAB SpecializationMathWorks

About this Course

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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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Start instantly and learn at your own schedule.

Course 3 of 4 in the

Practical Data Science with MATLAB Specialization

Intermediate Level

Approx. 22 hours to complete

English

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Skills you will gain

Machine Learning
Matlab
Predictive Modelling

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 3 of 4 in the

Practical Data Science with MATLAB Specialization

Intermediate Level

Approx. 22 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.84/5 (47 Ratings)

Offered by

MathWorks

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Syllabus - What you will learn from this course

Week

Week 1

5 hours to complete

Creating Regression Models

5 hours to complete

11 videos (Total 73 min), 8 readings, 7 quizzes

11 videos

Practical Data Science with MATLAB3m

Instructor Introduction2m

Introduction to Supervised Machine Learning4m

Introduction to the Taxi Data7m

Creating and Cleaning Features8m

Introduction to Regression8m

Using the Regression Learner App10m

Customizing Model Parameters9m

Evaluating Regression Models6m

Evaluate Your Model in MATLAB9m

Summary of Regression1m

8 readings

Access MATLAB15m

Data and Code Files15m

Supervised Machine Learning Reference10m

Introduction to Module 15m

Variables in the Taxi Data10m

Note regarding updates to MATLAB5m

Summary of Regression Models15m

Regression Metrics10m

3 practice exercises

Feature Engineering Review12m

Train a Regression Model30m

Apply the Regression Workflow45m

Week

Week 2

4 hours to complete

Creating Classification Models

4 hours to complete

6 videos (Total 45 min), 7 readings, 2 quizzes

6 videos

Introduction to Classification9m

Using the Classification Learner App7m

Evaluating Classification Models11m

Evaluating Classification Models in MATLAB5m

Training a Multiclass Model7m

Summary of Classification1m

7 readings

Introduction to Module 25m

Note regarding updates to MATLAB5m

Summary of Classification Models15m

Binary Classification Metrics Reference20m

Evaluate and Customize Classification Models30m

Multiclass Classification Metrics Reference20m

Customizing Multiclass Models30m

2 practice exercises

Train a Classification Model30m

Apply The Classification Workflow50m

Week

Week 3

8 hours to complete

Applying the Supervised Machine Learning Workflow

8 hours to complete

9 videos (Total 49 min), 5 readings, 3 quizzes

9 videos

Addressing Underfitting and Overfitting8m

Using Validation Data During Training3m

Embedded Methods for Feature Selection7m

Using Regularization to Prevent Overfitting6m

Introduction to Ensemble Models3m

Training Ensemble Models3m

Introduction to Hyperparameters5m

Optimizing Hyperparameters8m

Summary of Module 32m

5 readings

Introduction to Module 310m

Examining Bias Variance Trade-off15m

Practice Partitioning Data30m

Using Wrapper Methods to Select Features40m

Introduction to the Course Project10m

2 practice exercises

Practice Reducing Model Complexity30m

Applying Ensemble Models30m

Week

Week 4

5 hours to complete

Advanced Topics and Next Steps

5 hours to complete

5 videos (Total 26 min), 7 readings, 2 quizzes

5 videos

Handling Class Imbalance5m

Reducing Specific Errors Using Cost Matrices7m

Integrating Your Model3m

A Discussion with Heather7m

Summary of Predictive Modeling and Machine Learning3m

7 readings

Introduction to Module 45m

Sampling Data30m

Practice Handling Class Imbalance30m

Oversampling the Minority Class30m

Examples of Integrating Machine Learning Models15m

Automated Machine Learning45m

Provide Feedback on Your Course Experience5m

2 practice exercises

Practice Reducing Prediction Errors30m

Quiz: Advanced Topics and Next Steps1h

Reviews

4.8

26 reviews

5 stars
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4 stars
17.47%
3 stars
1.94%

TOP REVIEWS FROM PREDICTIVE MODELING AND MACHINE LEARNING WITH MATLAB

by SVJan 5, 2022

Thanks to Mathworks team for such a well structured course with quality content and lectures. Looking forward to more such quality content such as deep learning and reinforced learning

by ACDec 13, 2020

Great course, I like how they keep everything organized and pretty straightforward.

by JDOct 25, 2020

Great Course and very helpful. Good to be able to put hands on real data and exercises.

by MPMar 20, 2021

Helpful in defining data preprocessing and model creation using different mechanism

View all reviews

About the Practical Data Science with MATLAB Specialization

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.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Will I have access to MATLAB?
Yes. A free license to MATLAB Online is available to learners enrolled in the course. You can view the supported browsers here.

More questions? Visit the Learner Help Center.

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Predictive Modeling and Machine Learning with MATLAB

About this Course

Skills you will gain

Instructors

Michael Reardon

Maria Gavilan-Alfonso

Erin Byrne

Matt Rich

Brandon Armstrong

Adam Filion

Isaac Bruss

Nikola Trica

Brian Buechel

Heather Gorr

Sam Jones

Offered by

MathWorks

Syllabus - What you will learn from this course

Creating Regression Models

Creating Classification Models

Applying the Supervised Machine Learning Workflow

Advanced Topics and Next Steps

Reviews

TOP REVIEWS FROM PREDICTIVE MODELING AND MACHINE LEARNING WITH MATLAB

About the Practical Data Science with MATLAB Specialization

Frequently Asked Questions

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Predictive Modeling and Machine Learning with MATLAB

About this Course

Skills you will gain

Instructors

Michael Reardon

Maria Gavilan-Alfonso

Erin Byrne

Matt Rich

Brandon Armstrong

Adam Filion

Isaac Bruss

Nikola Trica

Brian Buechel

Heather Gorr

Sam Jones

Offered by

MathWorks

Syllabus - What you will learn from this course

Creating Regression Models

Creating Classification Models

Applying the Supervised Machine Learning Workflow

Advanced Topics and Next Steps

Reviews

TOP REVIEWS FROM PREDICTIVE MODELING AND MACHINE LEARNING WITH MATLAB

About the Practical Data Science with MATLAB Specialization

Frequently Asked Questions

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Start or advance your career

Popular Courses and Certifications

Popular collections and articles

Earn a degree or certificate online

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