> For the complete documentation index, see [llms.txt](https://opencampus.gitbook.io/opencampus-machine-learning-program/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/archive/python-from-beginner-to-practitioner/week-7.md).

# Week 7

### To-Do

Homework:

* Decide for one of the two final projects (they will be shown on your certificate)
  * Knowledge Cards: Flash Card Tool
  * Digital Pet: Interactive Virtual Companion
* List out what data the program has to handle (e.g. flash card with front and back, pet stats like hunger) and the matching data structures you need in python
* Create a flow chart for the program, like you have seen with hangman in the course:

<figure><img src="https://4020123021-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-MHobCAnoTQkN71lOgdv%2Fuploads%2FHGUynpMoUNlcb3YaJwcH%2FSolution%2B-%2BHangman%2BFlowchart%2B1(1).png?alt=media&amp;token=779d7ebe-c9a1-4038-87cc-0a6c6c4c5990" alt="Hangman Flow Chart" width="375"><figcaption><p>Flow Chart for the hangman program</p></figcaption></figure>

* We will form groups of \~5 people and you will get time to discuss together

***

### Totally Optional

* **Watch lecture 5 of the Havard Python Course:**

{% embed url="<https://cs50.harvard.edu/python/2022/weeks/5/>" %}

For the best learning experience, it's recommended to watch the lecture twice: first for a quick overview, and then more slowly while taking notes. Please ensure you allocate sufficient time for this.

Always first create a copy with "Copy to Drive" or download the notebooks to work locally on them. Otherwise your progress won't be saved!!


---

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