Payment Risk and Payment Fraud: Data Science and Analytics

Descripción

Hi, this is Kangxiao, I have many years of working experience with industry leaders like Paypal, Google, and Chime. Throughout my entire career, I have used data to do analysis, build models, and solve key business problems. When I learn online, I often run into two issues: • The course offers in-depth knowledge, but it doesn't have very broad coverage. In reality, we don't need to be experts for everything. But it will give us a huge advantage if we know the basics for a lot of things. • The course focuses too much on the technical side. I find a lot of the courses focus entirely on either coding like how to write Python codes, or stats like the math behind different kinds of ML models. And there are very few courses that link payment risk/fraud, modeling, and coding together to solve real-world problems. In the payment and payment risk industry, people have come to the conclusion that we have to rely on data-driven solutions to fight against the bad actors. This makes data science and data analytics super important for payment risk and payment fraud. Thus, In this course, I want to share my knowledge of data science and analytics in payment risk by offering very broad coverage of payment and payment risk basics, data science, statistics, modeling, and coding, and using case studies to connect data, coding, and stats together. That’s exactly what we do in the real world, in our day-to-day work. The best talents I observe in Paypal, Google, and Chime are the ones who are really good at connecting these dots together to solve complicated problems. I hope this course can help set you ready for your future success in payment and payment risk. Please join us, If any of these interests you. Let's enjoy this journey together!

Lo que aprenderás

• Understand how payment works in general
• Understand how fraudsters work, the different payment fraud types and corresponding risky signals
• Understand the statistic and ML basics
• Understand the SQL basics
• Understand the Python basics
• Complete one case study to build a decision tree model with Python to solve fraud problem
• Complete one case study to

Requisitos

• No experiences needed, we will learn everything from this course