Introduction To Data Science

Introduction To Data Science, available at $24.99, has an average rating of 3.5, with 28 lectures, based on 254 reviews, and has 4581 subscribers.

You will learn about Start and execute the steps of a data science project, from project definition to model evaluation. Use machine learning techniques to build effective predictive models. Learn how to find and correct common problems found in real world data. This course is ideal for individuals who are The course is for analytically minded students who are looking for an introduction to applied predictive modeling methods, and who want to learn about what goes into successful data science projects. The course will teach students how to use existing machine learning methods in R, but will not teach them how to implement these algorithms from scratch. Students should be familiar with basic statistics and basic scripting/programming. Some familiarity with R is helpful; otherwise, students should be willing to learn R as they go. We will direct you to ready-to-go implementations and additional references throughout the course. It is particularly useful for The course is for analytically minded students who are looking for an introduction to applied predictive modeling methods, and who want to learn about what goes into successful data science projects. The course will teach students how to use existing machine learning methods in R, but will not teach them how to implement these algorithms from scratch. Students should be familiar with basic statistics and basic scripting/programming. Some familiarity with R is helpful; otherwise, students should be willing to learn R as they go. We will direct you to ready-to-go implementations and additional references throughout the course.

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Summary

Title: Introduction To Data Science

Price: $24.99

Average Rating: 3.5

Number of Lectures: 28

Number of Published Lectures: 28

Number of Curriculum Items: 28

Number of Published Curriculum Objects: 28

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

• Start and execute the steps of a data science project, from project definition to model evaluation.
• Use machine learning techniques to build effective predictive models.
• Learn how to find and correct common problems found in real world data.

Who Should Attend

• The course is for analytically minded students who are looking for an introduction to applied predictive modeling methods, and who want to learn about what goes into successful data science projects. The course will teach students how to use existing machine learning methods in R, but will not teach them how to implement these algorithms from scratch. Students should be familiar with basic statistics and basic scripting/programming. Some familiarity with R is helpful; otherwise, students should be willing to learn R as they go. We will direct you to ready-to-go implementations and additional references throughout the course.

Target Audiences

• The course is for analytically minded students who are looking for an introduction to applied predictive modeling methods, and who want to learn about what goes into successful data science projects. The course will teach students how to use existing machine learning methods in R, but will not teach them how to implement these algorithms from scratch. Students should be familiar with basic statistics and basic scripting/programming. Some familiarity with R is helpful; otherwise, students should be willing to learn R as they go. We will direct you to ready-to-go implementations and additional references throughout the course.