Overview
Context of the Fraud Detection in R course at Data Camp
The Association of Certified Fraud Examiners estimates that fraud costs organizations worldwide $3.7 trillion a year and that a typical company loses five percent of annual revenue due to fraud. Fraud attempts are expected to even increase further in future, making fraud detection highly necessary in most industries.
Some techniques from robust statistics and digit analysis are presented to detect unusual observations that are likely associated with fraud.
Two main challenges when building a supervised tool for fraud detection are the imbalance or skewness of the data and the various costs for different types of misclassification.
We present techniques to solve these issues and focus on artificial and real datasets from a wide variety of fraud applications.
Programme Structure
Chapters
- Social network analytics
- Imbalanced class distributions
- Digit analysis and robust statistics
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Disciplines
Information Technology (IT) Machine Learning View 384 other Short Courses in Information Technology (IT) in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
PREREQUISITES
- Unsupervised Learning in R
- Supervised Learning in R: Classification
Tuition Fee
To always see correct tuition fees
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International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
Basic Access: Free; Premium (for individuals): $12.42 per month billed annually; Teams: $25 per month billed annually; Enterprise: Contact sales for pricing
Funding
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