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Programming in Python (for quantitative biologists) ¶
Learning objectives and expected learning outcomes ¶
The course introduces students to imperative programming by referring to the Python language.
The course is divided in two parts:
- Python and its object-oriented features;
- Python libraries that can be useful in scientific computation and data analysis, in particular NumPy and pandas.
Students will acquire the ability to write and tune a program that automatizes simple computational tasks; they will be able to understand how a small piece of Python code works, to find the reasons of a malfunction and to correct it appropriately. Moreover, students will be able to use the NumPy and pandas library to analyze tabular data.
A.A. 2022/23 ¶
The course will take place in the first semester. Currently, we expect to lecture on-premises, lectures will NOT be streamed. You can find some videos from last year course in the 2020/21 web page linked below. Since November 29, the lectures on both Tuesdays and Thursdays are in room G15.
Lessons Rooms Farina (Tu), G15 (Th) (40h) | Th_6/10 Tu_11/10 Th_13/10 | Tu_18/10 Th_20/10 | Tu_25/10 Th_27/10 | Th_3/11 Tu_8/11 Th_10/11 Tu_15/11 | Tu_22/11 Th_24/11 | Tu_29/11 Th_1/12 | Tu_6/12 Tu_13/12 Th_15/12 | Tu_20/12 Tu_10/1 |
---|---|---|---|---|---|---|---|---|
Labs, Room Delta (16h) | Fr_14/10 | Fr_21/10 | Fr_4/11 | Fr_18/11 | Fr_25/11 | Fr_2/12 | Fr_16/12 | Fr_13/1 |
Setup | Scaffolded | Plain Python interpreter | Notebooks |
Syllabus ¶
- The Python programming language.
- Native data types.
- Functions, selections and iterations.
- Basic data structures: lists, tuples, dictionaries.
- Object-oriented encapsulation.
- Iterators and generators.
- Files.
- Numpy multi-dimensional arrays and matrices.
- Data manipulation and analysis with pandas.
Any Python3 book can be used to support the learning of the general part, for example J. Hunt "A Beginners Guide to Python 3 Programming" (The electronic version is free for Unimi students). NumPy and pandas have excellent online documentation.
The examination is based on laboratory exercises. A final mark (on a 30 point scale) is given, by taking into account the knowledge of the subject and tools, and the clarity of the solutions.
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Programming in Python (for quantitative biologists)
- Learning objectives and expected learning outcomes
- A.A. 2022/23
-
2022/23
- 1. October 6 8:30 Room G15
- 2. October 11 10:30 Room Farina
- 3. October 13 8:30 Room G15
- 4. October 14 8:30 Lab Delta
- 5. October 18 10:30 Room Farina
- 6. October 20 8:30 Room G15
- 7. October 21 8:30 Lab Delta
- 8. October 25 10:30 Room Farina
- 9. October 27 8:30 Room G15
- 10. November 3 8:30 Room G15
- 11. November 4 8:30 Lab Delta
- 12. November 8 10:30 Room Farina
- 13. November 10 8:30 Room G15
- 14. November 15 10:30 Room Farina
- 15. November 18 8:30 Lab Delta
- 16. November 22 10:30 Room Farina
- 17. November 24 8:30 Room G15
- 18. November 18 8:30 Lab Delta
- 19. November 29 10:30 Room G15
- 20. December 1 8:30 Room G15
- 21. December 2 8:30 Lab Delta
- 22. December 6 10:30 Room G15
- 23. December 13 10:30 Room G15
- 24. December 15 8:30 Room G15
- 25. December 16 8:30 Lab Delta
- 26. December 20 10:30 Room G15
- 27. January 10 10:30 Room G15
- 28. January 13 8:30 Lab Delta
- Previous years ¶
2022/23 ¶
1. October 6 8:30 Room G15 ¶
2. October 11 10:30 Room Farina ¶
3. October 13 8:30 Room G15 ¶
4. October 14 8:30 Lab Delta ¶
5. October 18 10:30 Room Farina ¶
6. October 20 8:30 Room G15 ¶
7. October 21 8:30 Lab Delta ¶
- Triangle kinds
- DNA Hamming
- Newton square root
- If you want to understand a bit more of git and github you can also try this