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Python: automation, web scraping, image processing
Discover the possibilities of automation when working with data and images using Python. In three sessions of this interactive course, we will work together to learn the basics.
The internet is a huge source of information. Using web scraping, you can extract targeted data from websites to help you make decisions or analyse trends. In this course, you will learn how to use Python to extract data from the internet and then clean and prepare it.
In another session, we will look at analysing the data and how to convert it into different file formats and create appealing visualisations.
We will also look at image processing in Python and you will learn how to use Python to automate work steps.
General information
| Duration | 9 hours |
|---|
- Web scraping, data cleansing and data preparation
- Identifying and selecting relevant elements in HTML source code
- Web scraping (e.g. with BeautifulSoup)
- Cleansing and preparing data
- Analysing data, saving data in other file formats, presenting data
- Basic data analysis techniques with Python
- Saving data in different file formats
- Creating diagrams and visualisations
- Creating interactive dashboards (e.g. with Dash or Flask)
- Image processing and automation with Python
- Introduction to image processing with Python (e.g. with OpenCV)
- Simple manipulation of images
- Using Python to automate tasks and workflows
Basic knowledge of Python is required for this course. Participants should have successfully completed at least the "Python Basics" course. Participants should be familiar with the basics of Python programming, including variables, data structures (e.g. lists, dictionaries), loops and conditional statements.
In addition, it is helpful if you already have some experience with Python libraries. Knowledge of the following libraries would be an advantage, but is not essential:
In addition, it is helpful if you already have some experience with Python libraries. Knowledge of the following libraries would be an advantage, but is not essential:
- BeautifulSoup (for web scraping)
- Pandas (for data manipulation and analysis)
- Matplotlib (for data visualisation)
- OpenCV (for image processing)
This course is aimed in particular at employees who would like to deepen their Python skills. Participation is open to all members of the UZH.
At the end of the course, participants will be able to use Python for web scraping, data cleansing, data analysis, file conversion, data presentation, automation and image processing.
Participants will be able to create automated workflows, analyse data effectively and present results visually.
Participants will be able to create automated workflows, analyse data effectively and present results visually.
Teaching material will be provided during the course. Examples of possible projects can be found in this book: https://inventwithpython.com/bigbookpython/
Each course includes both theoretical explanations and practical exercises. The exercises allow participants to directly apply what they have learnt and consolidate their skills.
Dates
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