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Supervised Machine Learning: Regression and Classification AboutOutcomesModulesRecommendationsTestimonialsReviewsGain insight into a topic and learn the fundamentals.Flexible scheduleApprox. 33 hoursLearn at your own paceMost learners liked this courseGain insight into a topic and learn the fundamentals.Flexible scheduleApprox. 33 hoursLearn at your own paceMost learners liked this courseAboutOutcomesModulesRecommendationsTestimonialsReviewsWhat you'll learnBuild machine learning models in Python using popular machine learning libraries NumPy & scikit-learnBuild & train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regressionDetails to knowShareable certificateAdd to your LinkedIn profileSee how employees at top companies are mastering in-demand skillsBuild your subject-matter expertiseLearn new concepts from industry experts Gain a foundational understanding of a subject or toolDevelop job-relevant skills with hands-on projectsEarn a shareable career certificateEarn a career certificateAdd this credential to your LinkedIn profile, resume, or CVShare it on social media and in your performance reviewThere are 3 modules in this courseWelcome to the Machine Learning Specialization!  You're joining millions of others who have taken either this or the original course, which led to the founding of Coursera, and has helped millions of other learners, like you, take a look at the exciting world of machine learning!What's included20 videos1 reading3 assignments1 app item4 ungraded labsThis week, you'll extend linear regression to handle multiple input features.  You'll also learn some methods for improving your model's training and performance, such as vectorization, feature scaling, feature engineering and polynomial regression.  At the end of the week, you'll get to practice implementing linear regression in code.What's included10 videos2 assignments1 programming assignment5 ungraded labsThis week, you'll learn the other type of supervised learning, classification.  You'll learn how to predict categories using the logistic regression model.  You'll learn about the problem of overfitting, and how to handle this problem with a method called regularization.  You'll get to practice implementing logistic regression with regularization at the end of this week! What's included12 videos2 readings4 assignments1 programming assignment9 ungraded labsInstructorsDeepLearning.AI46 Courses8,126,985 learnersOffered byRecommended if you're interested in Machine LearningWhy people choose Coursera for their careerFelipe M.Learner since 2018"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."Jennifer J.Learner since 2020"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."Larry W.Learner since 2021"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go.""Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."Learner reviews4.926,210 reviews5 stars91.65%4 stars7.24%3 stars0.63%2 stars0.16%1 star0.29%Showing 3 of 262105Reviewed on Jan 28, 2025I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and Coursera.4Reviewed on Apr 30, 2023Optional Lab lot more time than mentioned without prior experience of python and libraries used. Its estimated  time should be change, it's a lot more than 1 hour. Video and exercises are very good.5Reviewed on Dec 13, 2024Andrew was a great teacher, explaining complicated topics in a simple and intuitive way. The programming assignments helped to put theory into practice. A great place to start learning a new field!New to Machine Learning? Start here.Open new doors with Coursera PlusUnlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscriptionAdvance your career with an online degreeEarn a degree from world-class universities - 100% onlineJoin over 3,400 global companies that choose Coursera for BusinessUpskill your employees to excel in the digital economyFrequently asked questionsAccess 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.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.More questions