Difference between revisions of "LU-pysem/CourseProject"
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==Course Project== |
==Course Project== |
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* '''enter your project topic by November 8, 2020''' |
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=== About the Course Project === |
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During the course, students are required to complete a project that accomplishes a non-trivial programming / data processing task using Python tools. |
During the course, students are required to complete a project that accomplishes a non-trivial programming / data processing task using Python tools. |
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* projects can be developed in teams of 2-3 people or individually. |
* projects can be developed in teams of 2-3 people or individually. |
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Data sets can come from a variety of sources, such as kaggle.com, data.gov.lv, or faculty. |
Data sets can come from a variety of sources, such as kaggle.com, data.gov.lv, or faculty. |
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All processing and visualization will have to be done in the Python programming language with the appropriate |
All processing and visualization will have to be done in the Python programming language with the appropriate Python libraries. |
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* you can use libraries covered in the course or/and from outside the course. |
* you can use libraries covered in the course or/and from outside the course. |
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Other topics may also be selected with prior agreement with the faculty. |
Other topics may also be selected with prior agreement with the faculty. |
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=== Final project presentations === |
=== Final project presentations === |
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Revision as of 12:45, 30 October 2020
Parent page: LU-pysem
Contents
Course Project
Submit your project topic:
Final project topic sign-up form (Autumn 2020):
- https://forms.gle/jPTMcEeGMfnpSFQk6
- enter your project topic by November 8, 2020
About the 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 Python 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.
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)
