Course curriculum

    1. 0.1 Welcome Screen

    2. 0.2 - How to use the Actuartech platform

    3. 0.3 How to get set up

    4. 0.4 - A User Guide for Jupyter Notebooks

    5. 0.5 - Other ways to code in Python

    6. 0.6 - Software and package requirements

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    1. 1.2 - Problem Specification

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    2. 1.3 - Background into the Models

    3. 1.4 - Further Reading

    1. 2.1 - Introduction

    2. 2.2 - Relevant Python Packages

    3. 2.3 - Preliminary Analysis and Reshaping of Data

    4. 2.4 - Conclusion

    1. 3.1 - Introduction

    2. 3.2 - Lee-Carter Model

    3. 3.3 - Cairns-Blake-Dowd Model

    4. 3.4 - Automating the Process

    5. 3.5 - Conclusion

    6. Week 1 Live Lesson: Chapter 1-3

    1. 4.1 - Introduction

    2. 4.2 - Deterministic Forecasting: Lee-Carter

    3. 4.3 - Deterministic Forecasting: Cairns-Blake-Dowd

    4. 4.4 - Stochastic Forecasting: Lee-Carter

    5. 4.5 - Stochastic Forecasting: Cairns-Blake-Dowd

    6. 4.6 - Conclusion

    1. 5.1 - Introduction

    2. 5.2 - Data Preparation

    3. 5.3 - Theoretical Background

    4. 5.4 - Fitting an LSTM using keras and tensorflow

    5. 5.5 - Further Advances when Fitting an LSTM using keras and tensorflows

    6. LSTM Notebooks, Lee-Carter & Cairns-Blake-Dowd Packages, and Dataset

    7. Week 2: Forecasting and Introduction to LSTM Neural Networks

About this course

  • £325.00
  • 44 lessons
  • 3 hours of video content