Sneak preview – Mooc – Bart Baesens – Credit Risk Analytics

Baesens_Bart_small     Big Data World
I had a nice lunch with Prof. Dr Bart Baesens today at the MIM to discuss his recent book ‘Analytics in a Big Data World: The Essential Guide to Data Science and its Applications’
One topic we discussed was knowledge transfer and certification.
Next to the recorded presentations already available on dataminingapps.com, the professor told me that his new course about Credit Risk Analytics would soon be released. Here is for you, in avant première, the content of this course that he has put together with SAS. This course will be available mid November 2014.

New e-learning course Credit Risk Analytics by professor Bart Baesens

The outline of the course is as follows:
Lesson 1: Introduction to Credit Scoring
Lesson 2: The Basel Capital Accords
Lesson 3: Preparing the data for credit scoring
Lesson 4: Classification for credit scoring
Lesson 5: Measuring the Performance of Credit Scoring Classification Models
Lesson 6: Variable Selection for Classification
Lesson 7: Issues in Scorecard Construction
Lesson 8: Defining Default Ratings and Calibrating PD
Lesson 9: LGD modeling
Lesson 10: EAD modeling
Lesson 11: Validation of Credit Risk Models
Lesson 12: Low Default Portfolios
Lesson 13: Stress testing
You are invited to send an email to Bart.Baesens@gmail.com if interested in more information.

One thought on “Sneak preview – Mooc – Bart Baesens – Credit Risk Analytics

  1. Beste Philippe,

    Na 6 maanden werk eraan, is het zover!
    Mijn E-learning cursus staat online op:

    https://support.sas.com/edu/schedules.html?id=1227&ctry=BE

    Laat gerust weten als je nog vragen zou hebben.

    PS. Ik heb momenteel een lijst van ongeveer 1000 man die ik nu kan beginnen mailen 😦

    Vriendelijke groeten,
    Bart

    Prof. Dr. Bart Baesens
    Faculty of Economics and Business
    KU Leuven
    Naamsestraat 69
    B-3000 Leuven
    Belgium

    http://www.dataminingapps.com
    Master of Information Management

    Like

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