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Fraud Detection in Python

Name: Fraud Detection in Python
Brand: Careervira
Price: 73 USD
Availability: InStock
Rating: 5.0 (3 reviews)

DataCamp

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Course Report

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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

Fraud costs an average company 5% of its annual revenues. This course will show you how to fight fraud using data. To identify fraud activity, you will be able to use both supervised and unsupervised learning techniques. Learn how to effectively deal with high-stakes data in fraud analytics. This course covers both theoretical and technical aspects. It also teaches you how to implement fraud detection methods. This course will provide you with tips and advice based on real-world experiences that can help you avoid common mistakes in fraud analytics.

Highlights

Rating & Reviews

Top 30 Percentile

Pedagogy

Top 30 Percentile

Parameters

Pedagogy

Acquire all major Python Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Python Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

Rating & Reviews

This highly acclaimed course is among the top-rated in Python Programming, 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 Python Programming.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Supervised Learning with scikit-learn

Unsupervised Learning in Python

What You Will Learn

Learn how to detect fraud using Python

You'll learn about the typical challenges associated with fraud detection, and will learn how to resample your data in a smart way, to tackle problems with imbalanced data

You will use classifiers, adjust them, and compare them to find the most efficient fraud detection model

You will segment customers, use K-means clustering and other clustering algorithms to find suspicious occurrences in your data

In this final chapter, you will use text data, text mining, and topic modeling to detect fraudulent behavior

Course Content

Expand all sections

Module 1: Introduction and preparing your data

Module 2: Fraud detection using labeled data

Module 3: Fraud detection using unlabeled data

Module 4: Fraud detection using text

Course Instructors

Charlotte Werger

Director of Advanced Analytics at Nike

Dr. Charlotte Werger currently works at Nike as a Director of Advanced Analytics. Charlotte is a data scientist with a background in econometrics and finance. She loves applying Machine Learning to a...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%