Poslední úprava: Hanus Luboš, Mgr., Ph.D. (18.02.2025)
There is no ONLINE version for SS 2024/2025
The course is taught in person and we expect students to come to the class to attend the lectures and seminars.
The aim of the course is to provide hands-on experience in programming in Python with a special emphasis on data manipulation and processing.
Students will get the basics of Pandas, Numpy or Matplotlib and collect web data with API requests. The students will also be guided through modern social-coding and open-source technologies such as GitHub, Jupyter and Open Data.
The students will gain experience using the data from the IES website and subject evaluation protocols.
The course would make use of the DataCamp online sources (https://www.datacamp.com) to provide the students with reliable yet simple resources for learning Python programming.
Poslední úprava: Hanus Luboš, Mgr., Ph.D. (18.02.2025)
Cíl předmětu -
Please switch to the english version.
Poslední úprava: SCHNELLEROVA (24.10.2019)
After passing the course, the students will be able to execute a software-based, data-oriented project in Python, specifically download the data from APIs or directly from the web, pre-process it, analyze it and visualize it. Further, they will be able to do it in a repeatable, standard software-development quality manner using version control.
Poslední úprava: Hronec Martin, Mgr., Ph.D. (06.02.2020)
Literatura -
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Poslední úprava: Krejcar Vilém, Mgr. (01.10.2024)
Book
Wes McKinney: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, O'Reilly, 2012
Important Note: To pass the course, students must achieve at least 50% of the points from both the work-in-progress presentation and homework assignments.
Grading scale (according to Dean's Provision 17/2018):
A: above 90 (not inclusive)
B: between 80 (not inclusive) and 90 (inclusive)
C: between 70 (not inclusive) and 80 (inclusive)
D: between 60 (not inclusive) and 70 (inclusive)
E: between 50 (not inclusive) and 60 (inclusive)
F: below 50 (inclusive)
Poslední úprava: Krejcar Vilém, Mgr. (01.10.2024)
Sylabus -
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Poslední úprava: Krejcar Vilém, Mgr. (01.10.2024)
Here’s your schedule with the semester beginning on February 17th:
WEEK
DATE
L/S
TOPIC
LECTURER
DEADLINE
1
17/2
S
Seminar 0: Setup (Jupyter, VScode, Git, OS basics)
Luboš
1
18/2
L
Python basics
Luboš
2
25/2
L
Python basics II
Luboš
2
26/2
S
Seminar 1: Basics
Vilém
3
3/3
L
Numpy
Luboš
HW 1
4
10/3
L
Pandas I
Luboš
4
11/3
S
Seminar 2: Numpy & pandas
Vilém
HW 2
5
17/3
L
Pandas II + Matplotlib
Luboš
5
18/3
S
Seminar 3: Data formats & APIs
Vilém
-
6
24/3
L
Data formats, APIs
Luboš
HW 3
7
31/3
-
MIDTERM
Luboš & Vilém
7
1/4
S
Seminar 4: Midterm solution
Vilém
8
7/4
L
Algorithmic problem solving
Luboš
9
14/4
L
Data science
Luboš
10
21/4
L
How to code (avoiding spaghetti code)
Luboš
10
22/4
S
Seminar 5: Data science case-study
Vilém
Project proposal approval
11
28/4
L
Mixed topics: pkg, tests, docs, sql
Luboš
12
5/5
L
Guest Lecture: TBA, Beer with the guest and class-members after the lecture at TBA, 8:15pm
Luboš & Vilém
13
12/5
-
14
19/5
-
15
26/5-28/5
-
WiP: Project consultations
Luboš & Vilém
16
2/6-6/6
-
WiP: Project consultations
Luboš & Vilém
17
9/6
-
18
16/6
-
Deadline Final Project - submit
Luboš & Vilém
Let me know if you need any other adjustments! ����
Poslední úprava: Hanus Luboš, Mgr., Ph.D. (02.02.2025)
Vstupní požadavky -
Please switch to the english version.
Poslední úprava: SCHNELLEROVA (24.10.2019)
Previous experience with general coding is assumed - 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.
Poslední úprava: Hronec Martin, Mgr., Ph.D. (06.02.2020)
Požadavky k zápisu -
Please switch to the english version.
Poslední úprava: SCHNELLEROVA (24.10.2019)
The course is primarily for master and advanced bachelor students.
Poslední úprava: Hronec Martin, Mgr., Ph.D. (04.10.2022)
