This is the course that covers almost the majority portion of data science from model building, data visualization and demonstration of the end-to-end application using machine learning.

I have developed this course for beginners who are just starting out in Data Science. This course is mainly focused on leveraging machine learning in the transaction monitoring area of Anti-Money Laundering to identify suspicious transactions. So this course is most beneficial to Compliance and AML/CFT professionals who want to know about Machine Learning and its application in their job arena. This course is also suitable for Data scientists who want to explore opportunities in AML/CFT as AML/CFT is currently a very hot topic. Every Financial Institution all around the world has to implement an Anti-Money Laundering mechanism in their organization or they have to suffer huge penalties.

In this course we are going to cover the following topics:

1. Introduction Machine Learning and its types

2. Brief History of Machine Learning

3. Application of Machine Learning

4. Concept of Anti-Money Laundering

5. Concept of Transaction Monitoring

6. Decision-Making Model for Transaction Monitoring

7. Advantage of Machine Learning over Rule-Based Transaction Monitoring

8. Development of Machine Learning Algorithm using Python

9. Data visualization with Tableau

10. Introduction to MLNET and its application

There are a lot of concepts to cover, a wide variety of knowledge to gain. This course will benefit you immensely if you are either beginner, a data scientist, or just a compliance and AML/CFT professional.

I hope to see you in this course.