Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
14 Hour(s) 16 Minute(s)
Language
English
Taught by
Gopal Prasad Malakar
Rating
Course Overview
Analytics /Machine Learning / Data Science: Statistical / Econometrics foundation, SAS Program details, Modeling demo
What is this course all about?
This course is all about credit scoring / logistic regression model building using SAS. It explains
There course promises to explain concepts in a crystal clear manner. It goes through the practical issue faced by analyst. Some of the discussion item would be
- How to clarify objective and ensure data sufficiency?
- How do you decide the performance window?
- How do you perform data treatment
- How to go for variable selection? How to deal with numeric variables and character variables?
- How do you treat multi collinerity scientifically?
- How do you understand the strength of your model?
- How do you validate your model?
- How do you interpret SAS output and develop next SAS code accordingly?
- Step by step workout - model development on an example data set
What kind of material is included?
It consists of video recording of screen (audio visual screen capture), pdf of presentations, Excel data for workout, word document containing code and Excel document containing step by step model development workout details
How long the course will take to complete?
Approximately 30 hours
How is the course structured?
It has seven sections, which step by step explains model development
Why Take this course?
The course is more intended towards students / analytics professionals to
- Get crystal clear understanding
- Get jobs in this kind of work by clearing interview with confidence
- Be successful at their statistical or analytical profession due to the quality output they produce
Course Content
- 10 section(s)
- 111 lecture(s)
- Section 1 Course Outline
- Section 2 Introduction to Credit Scoring / Credit Score card development
- Section 3 Data Design for Modelling
- Section 4 Data Audit - Make sure to check that data is right for the modelling
- Section 5 Variable Selection - Select important numeric and character variables
- Section 6 Multi Collinearity Treatment
- Section 7 Iterate for final model / Understand strength of the model
- Section 8 Strength of a Model and Model Validation Methods
- Section 9 Reject Inference - Developing application score on scored population
- Section 10 Appendix Topics (It will have contents based on student's demands)
What You’ll Learn
- Learn model development, Understand the science behind model development, Understand the SAS program required for various steps, Get comfortable with interpretation of SAS program output, See the step by step model development
Skills covered in this course
Reviews
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MMelina G Ruiz Pérez
I really like the content. Easy to follow
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AAbburi Jagadeesh
Thanks for putting such a wonderful course for us, This course is really helpful to those who start their career in credit risk and want to gain knowledge, but the biggest missing part I felt was live coding, live coding makes this course more and more helpful though it consumes time. Thanks
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SSyed Abbas Madad
It is a really useful course for the one who loves to do modeling with data by all means. appreciate such an in-depth effort of Gopal. The information was hardly available in any other resource of the internet world. but if you need one roof resource then this course is the one.
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HHazel
The instructor provides a thorough and sound way of building a statistical model. I applied what I learned for my work. It's very practical and helpful!
