365 Careers – Credit Risk Modeling in Python 2021

The course is appropriate for beginners. We begin with basic theory and data.-Process and solve the complete exercise gradually in in front of you. File Size: 3.16 GB

365 Careers – Credit Risk Modeling in Python 2021

All new course!!

Hi! We are glad you found us! Credit Risk Modeling in Python. Only online course that teaches how banks use data science modeling in Python To improve their performance and conform to regulatory requirements. If this interests you, then this is the course for you. in A career in data science. Here’s why:
· The instructor is a proven expert (PhD from the Norwegian Business school, who has taught in HEC, University of Texas, and Norwegian Business school are world-famous universities.
· The course is suitable for beginners. We start with basic theory and data.-Process and solve the complete exercise gradually in In front of you
· Everything we cover is up-To-Date and pertinent in today’s development of Python Modelle for the banking sector
· This is the only online course that shows the complete picture in Credit risk in Python This scorecard was created from scratch using state-of-the-art techniques.
· Here we show you how to create models that are compliant with Basel II and Basel III regulations that other courses rarely touch upon
· We are not going to work with fake data. The dataset in This course is a real deal-Example from around the world
· You get to differentiate your data science portfolio by showing skills that are highly demanded in The job market
· What is most important – you get to see first-How to solve a data scientist task in The real-World
Data science courses tend to cover multiple frameworks but skip the pre-Processing and the theoretical part. This is similar to learning to taste wine before opening a bottle.
We don’t do that. We want you to have a solid foundation. Our goal is to help you understand the theory and learn how to apply it.-Process data that doesn’t necessarily come in The ‘’friendliest’’ format, and of course, only then we will show you how to build a state of the art model and how to evaluate its effectiveness.
We will discuss several important data science techniques during the course.
– Weight of evidence
Information value
– Fine classing
– Coarse Classing
– Linear regression
Logistic regression
– Area Under Curve
– Curve for Receiver Operating Characteristic Curve
– Gini Coefficient
Kolmogorov-Smirnov
– Assessing population stability
– Maintaining a Model
You will also receive valuable resources to help you learn more than the video lessons.
· Lectures
· Notebook files
· Homework
· Quiz questions
· Slides
· Downloads
· Access to Q&A where you could reach out and contact the course tutor.
You can start today by signing up for the course. This could be a huge step in your career. in data science. This amazing opportunity is your chance to take advantage of it!
You are welcome to come inside!