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 #### GWU DNSC 6290
 
 ## Course Outline
-* [Lecture 1: Interpretable Machine Learning Models](https://github.com/jphall663/GWU_rml/blob/master/README.md#lecture-1-interpretable-machine-learning-models)
-* [Lecture 2: Post-hoc Explanation](https://github.com/jphall663/GWU_rml/blob/master/README.md#lecture-2-post-hoc-explanation)
-* [Lecture 3: Discrimination Testing and Remediation](https://github.com/jphall663/GWU_rml/blob/master/README.md#lecture-3-discrimination-testing-and-remediation)
-* [Lecture 4: Machine Learning Security](https://github.com/jphall663/GWU_rml/blob/master/README.md#lecture-4-machine-learning-security)
-* [Lecture 5: Machine Learning Model Debugging](https://github.com/jphall663/GWU_rml/blob/master/README.md#lecture-5-machine-learning-model-debugging)
-* [Lecture 6: Responsible Machine Learning Best Practices](https://github.com/jphall663/GWU_rml/blob/master/README.md#lecture-6-responsible-machine-learning-best-practices)
+* Lecture 1: Interpretable Machine Learning Models
+* Lecture 2: Post-hoc Explanation
+* Lecture 3: Discrimination Testing and Remediation]
+* Lecture 4: Machine Learning Security
+* Lecture 5: Machine Learning Model Debugging
+* Lecture 6: Responsible Machine Learning Best Practices
 
 ## Lecture 1: Interpretable Machine Learning Models