====== Problem Set 01: Python Warmup ======

  * **Released on:** 09/07
  * **Due on:** __09/14 (by midnight)__

The objective of the first pset is to familiarize with Python and the Jupyter notebook that we'll be using in this course.

You'll complete three exercises in a Jupyter notebook:

  - Implement a simple function
  - A brute-force approach to the Knapsack Problem
  - Approximate pi using Monte Carlo sampling


===== Obtain the pset =====

Read the [[:start|quick start guide first]].

Make sure the VM is up to date as indicated in [[:vm_documentation#Update_16.410_configuration|Updating the 16.410 VM]]. The folder ''pset1-python-warmup'' will appear in the ''~/jupyter/psets'' folder.

Open the Jupyter notebook with the desktop shortcut. Then navigate to psets > pset1-python-warmup > ProblemSet01_PythonWarmup.ipynb

Read the instructions in the notebook and complete with your answers.
See [[:jupyteripython_documentation|Jupyter/IPython documentation]] for more information about the Jupyter notebook.

Also remember that the first recitation (F 09/09) will cover how to use the virtual machine and the Jupyter notebook.

===== Submitting your pset =====

You need to submit the completed Jupyter notebook that contains your solutions in Stellar before the deadline.

Follow the instructions [[psets:pset_submission|here]] for instructions on how to do that.


===== Questions / doubts / technical problems =====

Remember that you can post questions in our [[https://piazza.com/class/irm6tyo9mlr7ee|Piazza Forum]]. Please do not post answers to the problems, though.

===== Updates =====

  * There is a typo in the Problem Set. The mean errors shown in the table at the end of the exercise are % errors, but the % sign is not shown (the errors are 100 times smaller). Look at the post in Piazza for more details.