PythonDataIES

Data Processing in Python (JEM207)

The course site for the Data Processing in Python from IES. See information on SIS. The course is taught by Martin Hronec, Jan Šíla and Alena Pavlova.

Communication

Please direct all questions at Alena Pavlova only.

Final project

WiP consultations

Please reserve your date and time of the consultation here.

Project - paring

Schedule

Week Date L/S Topic Lecturer Deadline
1 19.2. S Seminar 0: Setup (Jupyter, VScode, Git, OS basics) Martin + Alena  
1 20.2. L Python basics Martin  
2 27.2. L Python basics II Jan  
3 4.3. S Seminar 1: Basics Alena HW 1
3 5.3. L Numpy Jan  
4 12.3. L Pandas I Martin  
5 18.3. S Seminar 2: Numpy & pandas Alena HW 2
5 19.3. L Pandas II + Matplotlib Martin  
6 26.3. L Data formats, APIs Jan  
7 2.4. S Seminar 3: Data formats & APIs Alena HW 3
7 8.4. - MIDTERM Alena, Jan & Martin  
8 9.4 L Algorithmic problem solving Jan  
9 15.4. S MIDTERM solution Alena  
9 16.4. L Data science Martin  
10 23.4. L How to code (avoiding spaghetti code) Martin Project proposal
11 29.4. S Seminar 5: Data science case-study Alena  
11 30.4. L Databases Jan Topic approved
12 7.5. L CarmineOptions + Beer after lecture @ https://pivo-klub.cz/ Marek Hauzr  
13 12.-16.5. - WiP: Project consultations Alena, Jan & Martin  
14 20.-23.5. - WiP: Project consultations Alena, Jan & Martin  

Course requirements

The requirements for passing the course are homeworks (5pts), the midterm (25pts), work in-progress-presentation (10pts), and the final project - including the final delivery presentation (60pts). At least 50% from the homeworks assignments and work-in-progress presentation is required for passing the course.

Final project (60%)

Projects’ Evaluation criteria

Project work - presentation (10%)

Midterm exam (25%)

Live coding (80 minutes), “open browser”, no collaboration between the students. More details during the lecture the week before

Homework Assignments (5%)

Prerequisities

The course is designed for students who 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 to enter the course.

Credits

Passing the course is rewarded with 5 ECTS credits.