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University Admission Prediction Using Multiple Linear Regression

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5

(4)

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Course Features

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Duration

2 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

2 hours

Course Description

This guided, hands-on project will teach us how to train regression models that can predict the likelihood of a student being accepted at a university. This project can be used to determine the acceptance rate of individual students by using web-based applications.

Course Overview

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Virtual Labs

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International Faculty

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Case Based Learning

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Post Course Interactions

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Case Studies,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Train Artificial Neural Network models to perform regression tasks

Perform exploratory data analysis

Understand the theory and intuition behind regression models and train them in Scikit Learn

Understand the difference between various regression models KPIs such as MSE, RMSE, MAE, R2, adjusted R2

Course Instructors

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Ryan Ahmed

Adjunct Professor & AI Enthusiast

Ryan Ahmed is a professor who is passionate about education and technology. Ryan holds a Ph.D. degree in Mechanical Engineering from McMaster* University, with focus on Mechatronics and Electric Vehi...

Course Reviews

Average Rating Based on 4 reviews

5.0

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