Name: Supervised Machine Learning: Regression
Rating: 5 (8 reviews)

Module 1: Introduction to Supervised Machine Learning and Linear Regression This module introduces a brief overview of supervised machine learning and its main applications: classification and regression. After introducing the concept of regression, you will learn its best practices, as well as how to measure error and select the regression model that best suits your data.Module 2: Data Splits and Cross Validation There are a few best practices to avoid overfitting of your regression models. One of these best practices is splitting your data into training and test sets. Another alternative is to use cross validation. And a third alternative is to introduce polynomial features. This module walks you through the theoretical framework and a few hands-on examples of these best practices.Module 3: Regression with Regularization Techniques: Ridge, LASSO, and Elastic Net This module walks you through the theory and a few hands-on examples of regularization regressions including ridge, LASSO, and elastic net. You will realize the main pros and cons of these techniques, as well as their differences and similarities.

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Course Credibility

The completion of this certificate renders a certificate from Coursera, a global online learning marketplace that aims to provide life-transforming learning experiences to learners around the world. It offers a range of learning opportunities—from hands-on projects and courses to job-ready certificates, career credentials, and degree programs. Coursera partners with more than 200 leading universities and companies to bring flexible, affordable, job-relevant online learning to individuals and organizations worldwide.

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Corporate Sponsors

Course Review

Flexibility- Self/Instructor paced

Pedagogy

The professors associated with this course have degrees from renowned institutions in the field of computer science, machine learning and engineering. The course offers a great opportunity to study under experienced professors. The applicants get to be a part of a self paced delivery method that enhances the concepts and lets them learn in an innovative way. It is an intermediate level course that is conducted in an online mode. The course offers instructor moderated discussions that offer great opportunities to make and build connections. The learners get to enjoy the benefits of practical learning. The curriculum prepares the learners for a career in the real world.

Industry Relevant Curriculum

Personalised or Dedicated Guidance and Mentoring

Discussion Forums / Instructor moderated

Course Accessibility- Mobile/Desktop

International Faculty

Hands-on training

Case Based Learning

Projects- Capstone, Industry-Simulation

Hands on training

Virtual Labs

Career impact

This certification course will help the learners grow their skill set. The learners will get to learn some of the popular industry related skills that will help them sustain longer in this domain. This course will make the working professionals ready for the Future. The topics are relevant to today's Information Technology environment.The course contains instructor moderated discussions that helps the learners to enhance their knowledge by raising general and specific queries. The course offers a platform to all the learners so that they can correct their mistakes through discussions.

Career Transition

CV & Interview Preparation

Job Impact

Pricing

The course is 11 hours long and offers access to course material on laptop and desktop. It is priced at a higher amount as per the industry standards. However, this course offers Industry related assistance that can help the learners grow professionally, practical learning, instructor moderated discussions and since it is an accredited degree, the course is worth investing in. By the end of the program, the learners will be able to master the in-demand skills necessary to become an expert capable of understanding Exploratory Data Analysis, Machine Learning Algorithms, Statistics and Probability, Supervised Learning, Logistic Regression, Regression Analysis, Linear Algebra and Calculus.

Peer Average

Assessment

The assessment method involves completing practice quizzes, graded programming assignments as well as undertaking graded assignments with peer feedback under various modules, throughout the duration of the degree. These can be research-based or concept specific. The final assessment ends with a programming project. The evaluations are designed to ensure continuous learner engagement with the program and to encourage learning

Present/Absent

Project Based Grading

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Quizzes

Offered by Coursera, the course helps the learners to understand regression, one of the most important types of supervised machine learning modelling families. The key highlights of the course are instructor-moderated discussions. This course is specially designed for Degree Holders, Mid-Career Professionals, Professional Learners and Developers. Industries, tech-firms, start-ups and government agencies are some of the areas where one can work as an expert. It is a self paced course conducted in an online mode that helps the working professionals to upgrade their skill set by learning about the fundamentals and basics of machine learning followed by their application in the real world.

This course will teach you about Regression, which is one of the most important types supervised machine-learning modelling families. This course will show you how to create regression models that predict continuous outcomes. For comparisons between models, you'll also be able to use error metrics. You will also learn best practices like regularization and train and test splits.

Mark J Grover

Miguel Maldonado

Supervised Machine Learning: Regression by Coursera is top course for Artificial Intelligence & Data Science. It is an Online course and is Paid

Supervised Machine Learning: Regression

Supervised Machine Learning: Regression

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Careervira Take

Course Credibility

Pedagogy

Hands-on training

Career impact

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Assessment

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Instructors

Mark J Grover

Miguel Maldonado

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