Hands On Training

Anomaly Detection in R

DataCamp

(3)

1 Coupon Available

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Are you concerned about inaccurate or suspicious records in your data? An anomaly detection algorithm could be the solution. One of many methods that can be used for detecting unusual data points is the anomaly detection algorithm. It is crucial in protecting computer networks from malicious activity and detecting fraudulent activities. This course will show you how to use advanced algorithms for anomaly scoring such as the isolation factor and local outlier factors. The UCI Wine Quality dataset will contain anomaly detection algorithms that can be used to identify wines with unusual characteristics and detect thyroid disease cases based on abnormal hormone measurements.

Highlights

Hands on training

Top 20 Percentile

Rating & Reviews

Top 30 Percentile

Parameters

Hands on training

This course stands out as one of the top 20 percentile options in R for Data Science, offering unparalleled hands-on training. Learners gain practical experience and skills through immersive learning, preparing them for real-world challenges. It ensures a well-rounded skill set, catering to a range of learning preferences. With a focus on Hands on training and Capstone Projects / Industry-Simulation as well as essential Virtual Labs, this course is tailored to meet diverse educational needs.

Rating & Reviews

This highly acclaimed course is among the top-rated in R for Data Science, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in R for Data Science.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms

In this course, you'll explore statistical tests for identifying outliers, and learn to use sophisticated anomaly scoring algorithms like the local outlier factor and isolation forest

Course Content

Expand all sections

Module 1: Statistical outlier detection

Module 2: Distance and density based anomaly detection

Module 3: Isolation forest

Module 4: Comparing performance

Course Instructors

DataCamp Content Creator

Course Instructor

DataCamp offers interactive R, Python, Spreadsheets, SQL and shell courses. All on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of you...

Course Reviews

Average Rating Based on 3 reviews

5.0

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