# Inversion and Optimisation Coursework
It consists of four parts:
Part-A (15 pts): covers lecture 1
Part-B (45 pts): covers lectures 2-7
Part-C (15 pts): covers lecture 8
Part-D (25 pts): covers lecture 9-11
Instructions:
* This is independent work, you cannot work in groups.
* Please provide your answers in each of the four notebooks seperately.
* For questions that involve coding please include the output, printed output or graphs,
that show the correct behaviour of your implementation without the need to rerun your code. However you do need to make sure that your code _can_ be rerun by executing the relevant cells in (top-to-bottom) order.
* You are allowed to use NumPy and Scipy and any code from the lecture notes in your answers.
* For answers that involve mathematical equations, use the usual combination of markdown and latex, or, if your prefer, include a photo/scan of your handwritten answer in the notebook.
* Even if you’re not completely sure how to complete a part of the question, our advice is to submit something, even if it’s just your ideas on how to go about answering the question, as you could well score some marks.
* **NOTE**: do not wait to complete Part-D until the very last minute! As explained in the notebook it is recommended to implement a version that you have tested on a small data set first, well in advance of the deadline, as the final run may take several hours to complete.