Difference between revisions of "LU-pysem/CourseProject"

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(Final project presentations)
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'''Each group should send an email to uldis.bojars(at)lu.lv''' (with text "Python seminar" in the subject line) '''containing:'''
'''Before presenting: each group should send an email to uldis.bojars(at)lu.lv''' (with text "Python seminar" in the subject line) '''containing:'''


* project description (including a list of group members + info about the role of each participant)
* project description (including a list of group members + info about the role of each participant)

Revision as of 15:16, 7 September 2020

Course Project

During the course, students are required to complete a project that accomplishes a non-trivial programming / data processing task using Python tools.

  • projects can be developed in teams of 2-3 people or individually.


Possible project topics:

  • process, analyze, and/or visualize one or more datasets
  • develop a simple game
  • web or desktop application
  • ... other ideas ...

Data sets can come from a variety of sources, such as kaggle.com, data.gov.lv, or faculty.

All processing and visualization will have to be done in the Python programming language with the appropriate Pyhon libraries.

  • you can use libraries covered in the course or/and from outside the course.

Other topics may also be selected with prior agreement with the faculty.

Submit your project topic:

Final project topic sign-up form (Autumn 2020):

Final project presentations

Project presentation = during the last class


Project presentation = 5-10 min. presentation consisting of:

  • Introduction (what the work is about)
  • Project realization (what was programmed, what software was used)
  • Demonstrations of results

You have to show what the project has done in practice = show code and results.

 

Before presenting: each group should send an email to uldis.bojars(at)lu.lv (with text "Python seminar" in the subject line) containing:

  • project description (including a list of group members + info about the role of each participant)
  • developed source code (or its URL at Github, Gitlab etc)
  • work results (e.g. Jupyter notebook)