Lead Teaching Assistant for the Machine Learning Practical course - Edinburgh University - 2017-2019
- Heavily involved in creating all weekly teaching materials, usually in the form of Jupyter notebooks, in which the students were required to build their own deep neural networks from scratch in numpy in Term 1. Further, in Term 2, I am the main contributor of tutorials on Pytorch/Tensorflow as well as cloud computing guides and GPU cluster debugging tutorials.
- One of main teaching staff involved in designing/structuring the coursework. Furthermore, the main contributor that implements any and all coursework boilerplate code/tutorial notes/guides.
- Supervision of student groups on their deep learning projects in term 2, where students can choose any deep learning related topic and work on a research project, to be implemented in Pytorch/Tensorflow. The main output is a report in ICML paper format. This component requires supporting students in writing a concise, readable and compelling paper.
- Maintenance and development of the MLP github repo
- Marker for term 2 research projects.
- Support for technical issues with GPU Clusters and Compute Cloud providers.
Teaching Assistant in - Lancaster University - 2014-2015:
- Supporting the learning of students in the lab sessions via instruction and guidance
- Evaluating students coursework via marking and discussions with other teaching staff