Useful Links:

• Math 150 Homepage: Course schedule, Python lab schedule, past common exams, suggested problems, etc.

Note: Some links on the course webpage are not public; one must sign in to a TAMU email for access.

• Python Instructional Video Series  (Care of the Math Learning Center)

• Gradescope for lab hand-in and viewing returned work

Example Notebooks:

Lab 3 Example Notebook 

Lab 2 Example Notebook 

Turn-in Instructions: 

Please turn in your labs via Gradescope. Only one copy should be handed in per group, but all contributing students should be added to the submission using Gradescope's groups function. Either use the print preview function in Google Colab or use a .ipynb-->pdf converter site like vertopal AFTER RUNNING ALL YOUR CODE to obtain a pdf version of your work. Make sure all printouts, etc. are visible. 

Python Tips:

Here is a Jupyter Notebook file with some common Python/Juptyer pitfalls, and here is a video of me talking through it.

• Avoid importing the math package! The methods therein cannot be applied to symbolic variables, which are a feature of the SymPy package. 

• Make each line of code simple; don't try to do everything in a single line. This will facilitate troubleshooting.

• Learn to write out pseudo-code, or work an example on paper. By pseudocode, I mean step-by-step outline (likely using math words/symbols) of the algorithm you want to implement.

• Find ways to check your code (do work by hand, check with other code, use Desmos, etc.). This is a useful skill, deepening understanding while assuring your code is correct.