The course site for the Data Processing in Python from IES. See information on SIS. The course is taught by Martin Hronec and Vítek Macháček and supported from abroad by Jan Šíla.
If you have intention to do the course, request Data Camp access here
- check your spam folder for invititation email. There are still people who did not sign up, although invited.
Please direct all questions at Jan Šíla only. Before you do, read the FAQ below!!
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If you are on waiting list there is nothing we can do to enroll you. We managed to master somehow
python, but SIS is something else. We follow the rules. Students usully drop from the course during the first week of the semester so there is a good chance you will be able to register. -
The course is held in-person and there is by default no online option.
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Datacamp is available to all who are enrolled. If you drop the course, let JS know to vacate the slot.
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If you are junior to last BSc year/ MSc level, please consider your coding skills. If you just started coding (R or anything else), please consider signing up later on. We will still be here (hopefully) next semester as well.
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If you decide to drop out after the 2-week grace period, note that if you start DataCamp homework, you will be awarded "F" mark followin the university guidelines. Please, do consider this as well with regards to staying in the course. There might be others waiting for the spot.
| Date | Topic | who | Notes | HW | |
|---|---|---|---|---|---|
| 13/2 | Seminar 0: Setup | Martin | (Jupyter, VScode, Git, OS basics) | ||
| 14/2 | L1: Python basics | Martin | |||
| 21/2 | L2: Python basics + funcs | Martin | HW 1 | ||
| 27/2 | Seminar 1 | Martin | |||
| 28/2 | L3: Pandas & numpy | Vitek | HW 2 | ||
| 7/3 | L4: Pandas 2 | Vitek | HW 3 | ||
| 13/3 | Seminar 2 | Vitek | |||
| 14/3 | L5: API, Flask | Vitek | |||
| 21/3 | L6: MIDTERM | Jan | |||
| 27/3 | Seminar 3 | Vitek | |||
| 28/3 | L7: Data science + Matplotlib | Martin | |||
| 4/4 | L8: How to code (avoiding spaghetti code) | Martin | |||
| 10/4 | Seminar 4 | Martin | DEADLINE: topic approval | ||
| 11/4 | L9: Databases | Vitek | HW 4 | ||
| 18/4 | L10: Live coding | Jan - online | |||
| 25/4 | L11: Guest lecture + Python Beer | TBA | |||
| 2/5 | WiP project consultations | all | |||
| 9/5 | WiP project consultations | all |
The requirements for passing the course are DataCamp assignments (5pts), the midterm (25pts), work in-progress-presentation (10pts), and the final project - including the final delivery presentation (60pts). At least 50% from the DataCamp assignments and work-in-progress presentation is required for passing the course.
- Students in teams by 2
- Deadline for topic approval: 10 April 2023
- Deadline: end of semester
- Use of git by both - 5pts
- meaningful commit messages
- pythonic code principles - 5 pts
- code is more often read than written, EAFP
- runability - 15 pts
- by far the most important one! Project needs to run from scratch after installing versioned requirements.
- code structure - 15 pts
- functions (classes), properly named variables
- README, documentation - 5 pts
- analysis, visualization - 15 pts
- highlight key poins of your projet
- Presentation of work-in-progress related to the final project.
- Prepare questions, understand the goals of your project
Takes place TBA - Live coding (80 minutes), "open browser", no collaboration between the students. More details during the lecture week before
At least 3 out of 4 assignments submitted on time is required.
- Introduction to Python - Python Basics
- Introduction to Python - Python Lists
- Introduction to Python - Functions and packages
You should have access to those. If not, let us know.
Introduction to Data Visualization
Interactive Data Visualization in Bokeh
Introduction to SQL for Data Science
Introduction to Databases in Python
The course is designed for students that have at least some basic coding experience. It does not need to be very advanced, but they should be aware of concepts such as for loop ,if and else,variable or function.
No knowledge of Python is required for entering the course.
Passing the course is rewarded with 5 ECTS credits.