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[udemy] Payment Risk and Payment Fraud: Data Science and Analytics
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 99 Lectures ( 8h 43m ) | Size: 6 GB
We will learn Modeling and Coding (SQL/Python) Knowledge
for Data Science and Data Analytics in Payment Risk
What you'll learn
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
Requirements
No experiences needed, we will learn everything from this course
Who this course is for:
Beginners who want to start a career in Payment & Payment Risk
Beginners who want to do payment risk and fraud analytics
Beginners who want to do payment risk and fraud data science
Anyone who is passionate about mitigating risk and catch fraud with data
Download
UsersDrive
ClicknUpload
UptoBox
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 99 Lectures ( 8h 43m ) | Size: 6 GB
We will learn Modeling and Coding (SQL/Python) Knowledge
for Data Science and Data Analytics in Payment Risk
What you'll learn
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
Requirements
No experiences needed, we will learn everything from this course
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!
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!
Who this course is for:
Beginners who want to start a career in Payment & Payment Risk
Beginners who want to do payment risk and fraud analytics
Beginners who want to do payment risk and fraud data science
Anyone who is passionate about mitigating risk and catch fraud with data
Download
UsersDrive
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ClicknUpload
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