All of the materials linked on this page are available on the original GitHub site developed for the course.

Lectures | Slides | videos | jupyter notebooks | other resources |
---|---|---|---|---|

1. Analyzing COVID-19 Data (March 30, 2020) |
Video: 3Blue1Brown:Simulating an Epidemic |
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2. Modelling Exponential Growth (April 1, 2020) |
Lecture 2 Slides | Lecture 2 Video | Exponential and Logistic Growth | |

3. Probability (April 6, 2020) |
Lecture 3 Slides | Lecture 3 Video | Modelling Recovery with Probability |
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4. Random Walk Models (April 8, 2020) |
Lecture 4 Slides | Lecture 4 Video | Random Walks |
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5. Characterizing Variability (April 13, 2020) |
Lecture 5 Slides | Lecture 5 Video | Variability and Custom Types | |

6. User-defined Types (April 15, 2020) |
Lecture 6 Slides | Lecture 6 Video | Defining New Types | |

7. Markov Chains and Continuous Random Variables (April 22, 2020) |
Lecture 7 Slides | Lecture 7 Video |
Markov Chains and Continuous Random Variables |
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8. Continuous Time (April 27, 2020) |
Lecture 8 Slides | Lecture 8 Video | Continuous Time |
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9. Exponential Distribution (April 29, 2020) |
<none> | Lecture 9 Video | Exponential Distribution |
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10. Differential Equations (May 4, 2020) |
Lecture 10 Slides | Lecture 10 Video | <none> |
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11. Optimization and Fitting to Data (May 6, 2020) |
Lecture 11 Slides | Lecture 11 Video | <none> |
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12. Networks in Epidemic Modelling (May 11, 2020) |
Lecture 12 Slides | Lecture 12 Video | Networks |
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Code content is licensed under the MIT license.

Text content is licensed under the CC BY-NC-SA license.