Miscellaneous TODO

[lucydot]

Technology

• Move to Quarto: https://nbdev.fast.ai/tutorials/blogging.html

Additional material

• include a comparison of numpy array vs Python lists to see the speed-up advantage
• include the Monte Carlo estimating Pi from code refinery in a randomness lesson: https://coderefinery.github.io/jupyter/first-notebook/ (also see the computational physics book)
• Teach integrals and derivatives as part of self-assessment for getting started part of the course (write own function for this with for, if, while, numpy)
• include one lesson on molecular dynamics (see work from Miguel) and the Verlet alogorithm (for solving ODEs) - https://physics.weber.edu/schroeder/md/
• Good question at start of Chapter 2 here for testing the Python basics and for practising searching for relevant methods: https://belglas.files.wordpress.com/2018/03/cpwp.pdf

Pedagogy

• Include more visual work for the ODE/PDE section - for example drawing grids and using them to explain what is happening as moving through the programme.

Re-structuring

• move rounding errors to an earlier section
• move assert statements to an earlier section

Assessment

• Move to more project-based coursework. Simulate MD (verlet alogorithm for time integration), from Miguel's work. Upload to Github (private repo) for assessment. Write tests and documentation.

Misc.

• Reference Donald knuth: literate programming "Instead of imagining that our main task is to instruct a computer what to do, let us concentrate rather on explaining to human beings what we want a computer to do."
• Reference scientific visualisation book: https://github.com/rougier/scientific-visualization-book

Bugs

• The version control lesson did not work so well due to technological glitches (didn't push or pull): need to work out how permissions are set, need to NOT create a README or license as I think this complicates the communication between the two