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## Updates

- Schedule -> Pushed back
- Course overview -> Small changes to tutorial order
- Module 1 -> mostly complete
- Module 2 -> Started
- Planned formats of material
		1. Markdown
		2. Latex
		3. Notebook - Interactive

---
## Topics
and questions

- Jupyter Notebook 
	- Python Jupyter lab notebooks will be made once markdown files are complete.
	- Alternative: Independent Jupyterlab notebooks as separate interactive assignment.
	- My Goal -> To make course available in different formats (notebook, pdf, html?) to allow students to choose their own learning environment that suits their preference.
	- Pros & cons:
		- + Interactive
		- + Good for teaching
		- - Slow

- GitHub Education Pack
	- Autograding feature like matlab grader. Requires Github understanding.

 - Extent of Git and Github integration in course
	 - Learn by doing -> Teach git early to keep track of their code throughout the course.

- Created "MiniProjects" List

- Project Assignment
	- inspired by Dr. Carlos Montalvo numerical methods textbook.
	- Every engineering problem: dependent variable = function(independent variables, parameters, forcing functions)
	- 3 page report.
	- No code is shown throughout the report until the appendix.
		- Intro
		- Theory - Math model
		- Results
		- Appendix - All the code

---
## Discussion 

- Gantt chart -> more detailed for tutorial
- Current Gantt chart needs updated
- Working over the summer not needed


- Move Git & Github in Module 2
		Github education -> Too many tools 

- Move to Notebook and use that instead of Spyder.

---
## Actions

- Convert a .md file tutorial to a jupyter notebook file.
- Make a Gantt chart for the Modules: 1-5 spread them around to be done by November with all tutorials for all modules
- Tie concepts from each module to practical problems (take a first crack at it -> we will revise it during our next meeting)
- Descibe a bit Github. Let's boil it down to: Github is a repository with a bunch of resources. students need to know how to search for it, download/fork the repository, run the code on their own computer, submit modifications back to their repository.