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.
Jan Šíla on the bench.
| Date | Topic | who | Notes | HW | |
|---|---|---|---|---|---|
| 3/10 | Seminar 0: Setup | Martin | (Jupyter, VScode, Git, OS basics) | ||
| 4/10 | Python basics | Vitek | |||
| 11/10 | Numpy & Pandas | Martin | HW 0&1 | ||
| 17/10 | Seminar 1 | Vitek | |||
| 18/10 | Advanced Pandas & Matplotlib | Vitek | HW 2 | ||
| 25/10 | DBs | Vitek | HW 3 | ||
| 31/10 | Seminar 2 | Vitek | |||
| 1/11 | Live coding example | Martin | |||
| 8/11 | Deployment, packaging & testing | Martin | HW 4 | ||
| 14/11 | MIDTERM | both | |||
| 15/11 | Seminar 3 | Martin | |||
| 22/11 | Flask, APIs | Vitek | |||
| 28/11 | Seminar 4 | Vitek | DEADLINE: topic approval | ||
| 29/11 | Data science libraries | Martin | |||
| 6/12 | Putting it all together | Martin | |||
| 13/12 | Guest lecture | TBA | |||
| 19/12 | WiP projectg consultations | both | |||
| 20/12 | WiP projectg consultations | both |
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: 28th of November 2022
- Deadline: 7th of February 2023
- Presentation of work-in-progress related to the final 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 Git for Data Science
Intermediate Python for Data Science
Manipulating DataFrames with pandas
Merging DataFrames with pandas
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.