Statistics for Risk Modeling (SRM)

Statistics for Risk Modeling (SRM)

₹22,100.00

SRM – Statistics for Risk Modeling  – Regular Lectures
Faculty: Shivangee Agarwal
Course Duration: 125+ hours

Category:

This course is meticulously crafted to prepare candidates for the Statistics for Risk Modeling (SRM) Exam, which evaluates your ability to utilise various statistical methods and models to analyse data effectively.

Key Topics:

  • Regression and Time Series Models: Techniques for predicting and analyzing trends over time.
  • Principal Components Analysis: Methodology for reducing dimensionality in data.
  • Decision Trees: Tools for making decisions based on data characteristics.
  • Cluster Analysis: Techniques for classifying and grouping data.
  • Model Selection and Validation: Processes for choosing the best models and ensuring their accuracy and reliability.

This course ensures that you are well-prepared to demonstrate your ability to apply these statistical methods and models, pivotal for successful risk modelling and actuarial work.

WHAT YOU WILL GET

Course Deliverables

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Recorded lectures
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Soft copy of resources
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Weekend Live classes
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Access to Student dashboard
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100% Placement & Training Assistance
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Technical support
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Practice papers
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Chapter wise MCQ Bank
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Course extension (2 more terms)
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Interactive Q&A Forum

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FACULTY

Meet The Instructor


Gaurav Kumar Patwary is a risk management professional with over two years of experience in model risk management for quantitative finance-based models used in the Asset Management division of a multinational bank. He holds a Bachelor’s degree in Economics from St. Xavier’s College, Kolkata, and a Master’s degree in Economics from Delhi School of Economics. Additionally, he has cleared 7 out of 13 actuarial papers from the IAI. During his work, he has also gained hands-on experience in Python, developing codes to test and challenge various aspects of models, further enhancing his technical skillset. His academic background and industry experience provide a strong foundation in statistics, economics, and finance.

PLAYLIST

Demo Class Videos