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FinTech remains one of the top hiring industries for Data Science. Standing out in the job market requires a portfolio of work around several important problems, one such being

Probability of Default
Credit Score Analysis

How is it different from a Kaggle Project or YouTube Project:

Dataset is NOT PUBLICLY available and is created by mentors that contains real world features.
We will look into industry-standard techniques on reducing dimensions
We will check out various trade-offs to select a ML technique for prediction of PD and Scorecard Development.
We will dive into Deployment using AWS Airflow.
We will observe how the post deployment processes are done:
Model Monitoring
Model Benchmarking & Stress-testing
And if the model is not stable, we will see Model re-tuning & recalibration
Create Technical document on Google Docs or Notion following guidelines.

We are booked for 30th Nov'2024 cohort. Next batch will start on 28th Dec'2024.

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