Difference between revisions of "LU-pysem"
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= Seminar: Getting things done with Python = |
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= Specseminārs: Python un citi zvēri = |
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In this seminar you will learn about the Python programming language, its libraries and frameworks. |
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Specseminārā tiks iepazīti Python programmēšanas valoda kā arī tās bibliotēkas un ietvari. Semināra mērķis ir dot ieskatu gan valodā, tās iespējās, gan plašajā pielietojumu lokā. Seminārā Python tiks lietots dažādu datu apstrādei un vizualizācijai. |
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The goal of the seminar is to give participants an insight into Python programming language and what can be done with it (including how it is used in practice). You will also learn how to use Python for data analysis and visualization. |
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===Kāpēc Python?=== |
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* Ērti lietojams un efektīvs. Izstrādāts labi lasāmam un ātri rakstāmam pirmkodam. |
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* Elastīgs. Gan iesācējiem, gan profesionāļiem. Var atbalstīt dažādas programmēšanas paradigmas. |
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* Populārs, labi un aktīvi atbalstīts. |
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* Lieto gan lielās gan mazās kompānijās un organizācijās pasaulē. |
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* Vairākos kursos jau lieto, un ne tikai DF |
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Specseminārā tiks iepazīta Python programmēšanas valoda kā arī tās bibliotēkas un ietvari. Semināra mērķis ir dot ieskatu gan valodā, tās iespējās, gan plašajā pielietojumu lokā. Seminārā Python tiks lietots dažādu datu apstrādei un vizualizācijai. |
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=== Saturs === |
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Pamatā divas daļas: |
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* Ievads Python programmēšanas valodā (kas ir Python) |
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** Pieņemot ka programmēšanas principi un vēlams kāda cita valoda jau ir zināmi |
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* Praktisks apskats ar piemēriem (kā un kur lieto Python) |
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** Rīki, bibliotēkas, ietvari, piemēram: IPython, Jupyter notebook, PyCharm, NumPy, SciPy, Pandas, Matplotlib, Flask, ... |
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'''Python seminar will continue in the next (Spring 2020) semester''' |
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====Studentu darbi==== |
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* It will take place on Fridays @ 14:30 in room 345 (LU, Raiņa bulv. 19) |
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Kursā studentiem būs jāapstrādā kāda datu kopa, jāveic tās analīze, un vizualizācija. Datu kopas var nākt no dažādiem avotiem, piemēram, [https://www.kaggle.com/datasets kaggle.com], vai pasniedzējiem. Visa apstrāde un vizualizācija būs jāveic Python programmēšanas valodā ar attiecīgajām bibliotēkām, kas tiks apskatītas kursā. |
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* First lecture: 07-Feb-2020 |
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* '''everyone must join Slack and fill out seminar registration form''' |
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''You can also join if you did not participate in the Python seminar before.'' --> |
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=== Organizē === |
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Semināru vada Leo Seļāvo, (pārsvarā attālināti) |
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Semināru atbalsta ar (iespējamām) lekcijām klātienē: |
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* Uldis Bojārs (LU DF) |
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* Jānis Zuters (LU DF, par mašīnmācīšanos) |
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* Normunds Gruzītis (LUMII, par NLP) |
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* Valdis Saulespurēns (Riga Coding School) |
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* un citi… |
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=== Komunikācija=== |
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Slack pierakstīšanās: http://bit.ly/py-lu-df |
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'''Important links:''' |
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= Kalendārs = |
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* this page: http://selavo.lv/pysem |
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* [https://docs.google.com/presentation/d/1yxaR_ZL3K6Z0QtOQM2dkQKXFEKGXldfy_4xsHkHWP3w/edit?usp=sharing Introduction slides (English)] |
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'''1. nodarbība:''' būs ceturtdien 13.09 @ 14:30 – vieta: Raiņa 19, 312. telpa. |
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'''Exams (presentation of the course project) will take place:''' |
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===[https://calendar.google.com/calendar/embed?src=9mkh6ja5ceutv9c1dvoc3cq290%40group.calendar.google.com&ctz=Europe%2FRiga Saite uz kalendāru] === |
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* on 08-Jan-2021 and 22-Jan-2021 at 14:00 |
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** location: online (Zoom) |
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* you can also present the course project at the last lecture (18-Dec-2020) |
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= Nodarbību materiāli = |
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* Ievads Python: [https://github.com/ValRCS/LU-pysem Lekcijas satura uzmetums] |
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Presentation sign-up form: |
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= Resursi = |
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* https://forms.gle/joPBuJWeo4os5MXr6 |
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* [https://www.anaconda.com/download/#macos Anaconda lejuplāde] |
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<!-- Course registration form (Autumn 2020): https://forms.gle/FBGsJiS6CxA8eQZu5 |
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Slack channel (discussion space): [https://join.slack.com/t/pythonludf/shared_invite/zt-h5jgmncj-HztHdIwet3Xrgxei8hgnBw link for joining Slack] |
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--> |
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<!-- |
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* Presentation topic signup form: https://forms.gle/46Liu7bSQJKUpy31A |
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* Final project signup form: https://forms.gle/LrMprE4Spx3qJ6BY6 |
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--> |
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==Information and Resources== |
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'''Seminar takes place on Fridays @ 14:45''' |
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* location: room 336 (LU, Raiņa bulv. 19) |
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* first seminar: 11-Sept-2020 |
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Slack channel: |
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* https://pythonludf.slack.com |
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=== Seminar materials === |
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Seminar materials will be published in the GitHub repository: |
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* https://github.com/ValRCS/ValRCS-LU_PySem_2020_2 |
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Last years' repositories: |
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* (Spring 2020) https://github.com/ValRCS/LU_PySem_2020_1 |
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* (Autumn 2019) https://github.com/ValRCS/LU_PySem_2019 |
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=== Presentations === |
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Presentation sign-up form: |
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* https://forms.gle/joPBuJWeo4os5MXr6 |
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==Course Requirements and Grading== |
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* '''Course Project (in groups of 2-3 students or individually)''' = up to 7 points (out of 10) |
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** Project should be a Python program or a Jupyter notebook |
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** ''Scope: project theme examples will be discussed in lectures'' |
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* '''Presentations and participation in class''' = up to 4 points |
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** Presentation on a cool Python library or project = 1..3 points each (2 presentations possible) |
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*** 3 points = long and serious presentation (30 min) |
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*** 2 points = medium presentation (10-15 min) |
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*** 1 point = short presentation |
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*** everyone needs to present at least once |
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** Participation in class = 1 point |
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*** ... or/and Python exercises solved on Project Euler, www.codewars.com, other exercise sites |
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* '''Attend at least 50% of seminars''' |
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* '''Submitted course evaluation in LUIS''' (mandatory) |
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''Note: sign up for presentations ahead of time'' |
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==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. |
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More information: [[LU-pysem/CourseProject|Course Project]] |
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==Why Python?== |
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* Python is easy to use and effective. |
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* Its code is easy to read and write. |
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* Python is a flexible language that can support many programming paradigms. |
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* Suitable for beginners and professionals alike. |
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* Popular and well-supported. |
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* Used by large and small companies and organizations worldwide. |
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* Used in many courses and workshops. |
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== Contents == |
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The seminar consists of two parts: |
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* Introduction to the Python programming language (What is Python) |
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** Assumption: participants know the basics of programming and, preferably, already know other programming languages |
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* Practical applications of Python, with examples (Getting things done with Python) |
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** Tools, libraries, frameworks ("batteries included") |
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*** [https://jupyter-notebook.readthedocs.io/en/stable/notebook.html Jupyter notebook], IPython environment |
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*** [https://www.anaconda.com/download/ Anaconda Python distribution] |
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*** Libraries: NumPy, SciPy, Pandas, Matplotlib, Flask, ... |
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== Organizers == |
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This seminar is lead by Uldis Bojārs and Valdis Saulespurēns. |
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Experts who might present guest lectures at the seminar: |
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* [[User:Leo | Leo Seļāvo]] (LU DF) |
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* Jānis Zuters (LU DF, on machine learning) |
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* Pēteris Paikens (LU MII) |
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* ... |
Latest revision as of 15:55, 2 December 2020
Seminar: Getting things done with Python
In this seminar you will learn about the Python programming language, its libraries and frameworks.
The goal of the seminar is to give participants an insight into Python programming language and what can be done with it (including how it is used in practice). You will also learn how to use Python for data analysis and visualization.
Specseminārā tiks iepazīta Python programmēšanas valoda kā arī tās bibliotēkas un ietvari. Semināra mērķis ir dot ieskatu gan valodā, tās iespējās, gan plašajā pielietojumu lokā. Seminārā Python tiks lietots dažādu datu apstrādei un vizualizācijai.
Important links:
Exams (presentation of the course project) will take place:
- on 08-Jan-2021 and 22-Jan-2021 at 14:00
- location: online (Zoom)
- you can also present the course project at the last lecture (18-Dec-2020)
Presentation sign-up form:
Information and Resources
Seminar takes place on Fridays @ 14:45
- location: room 336 (LU, Raiņa bulv. 19)
- first seminar: 11-Sept-2020
Slack channel:
Seminar materials
Seminar materials will be published in the GitHub repository:
Last years' repositories:
- (Spring 2020) https://github.com/ValRCS/LU_PySem_2020_1
- (Autumn 2019) https://github.com/ValRCS/LU_PySem_2019
Presentations
Presentation sign-up form:
Course Requirements and Grading
- Course Project (in groups of 2-3 students or individually) = up to 7 points (out of 10)
- Project should be a Python program or a Jupyter notebook
- Scope: project theme examples will be discussed in lectures
- Presentations and participation in class = up to 4 points
- Presentation on a cool Python library or project = 1..3 points each (2 presentations possible)
- 3 points = long and serious presentation (30 min)
- 2 points = medium presentation (10-15 min)
- 1 point = short presentation
- everyone needs to present at least once
- Participation in class = 1 point
- ... or/and Python exercises solved on Project Euler, www.codewars.com, other exercise sites
- Presentation on a cool Python library or project = 1..3 points each (2 presentations possible)
- Attend at least 50% of seminars
- Submitted course evaluation in LUIS (mandatory)
Note: sign up for presentations ahead of time
Course Project
During the course, students are required to complete a project that accomplishes a non-trivial programming / data processing task using Python tools.
More information: Course Project
Why Python?
- Python is easy to use and effective.
- Its code is easy to read and write.
- Python is a flexible language that can support many programming paradigms.
- Suitable for beginners and professionals alike.
- Popular and well-supported.
- Used by large and small companies and organizations worldwide.
- Used in many courses and workshops.
Contents
The seminar consists of two parts:
- Introduction to the Python programming language (What is Python)
- Assumption: participants know the basics of programming and, preferably, already know other programming languages
- Practical applications of Python, with examples (Getting things done with Python)
- Tools, libraries, frameworks ("batteries included")
- Jupyter notebook, IPython environment
- Anaconda Python distribution
- Libraries: NumPy, SciPy, Pandas, Matplotlib, Flask, ...
- Tools, libraries, frameworks ("batteries included")
Organizers
This seminar is lead by Uldis Bojārs and Valdis Saulespurēns.
Experts who might present guest lectures at the seminar:
- Leo Seļāvo (LU DF)
- Jānis Zuters (LU DF, on machine learning)
- Pēteris Paikens (LU MII)
- ...